Research Publications

Links to Publication Pages

Google Scholar: http://scholar.google.co.in/citations?user=XK5GUiYAAAAJ

ResearchGate Paper: http://www.researchgate.net/profile/Gajendra_Raghava/publications

Scopus: http://www.scopus.com/authid/detail.url?authorId=7003507401

1. Lathwal, A., Kumar, R., & Raghava, G. P. S. (2021). In-silico identification of subunit vaccine candidates against lung cancer-associated oncogenic viruses. Computers in Biology and Medicine, 130, 104215.

2. Patiyal, S., Kaur, D., Kaur, H., Sharma, N., Dhall, A., Sahai, S., Agrawal, P., Maryam, L., Arora, C., & Raghava, G. P. S. (2020). A Web-Based Platform on Coronavirus Disease-19 to Maintain Predicted Diagnostic, Drug, and Vaccine Candidates. Monoclonal Antibodies in Immunodiagnosis and Immunotherapy, 39(6), 204–216.

3. Kumar, R., Lathwal, A., Kumar, V., Patiyal, S., Raghav, P. K., & Raghava, G. P. S. (2020). CancerEnD: A database of cancer associated enhancers. Genomics, 112(5), 3696.

4. Dwivedi, V. D., Arya, A., Yadav, P., Kumar, R., Kumar, V., & Raghava, G. P. S. (2020). DenvInD: dengue virus inhibitors database for clinical and molecular research. Briefings in Bioinformatics, bbaa098.

5. Agrawal, P., Mishra, G., & Raghava, G. P. S. (2020). SAMbinder: A Web Server for Predicting S-Adenosyl-L-Methionine Binding Residues of a Protein From Its Amino Acid Sequence. Frontiers in Pharmacology, 10, 1690.

6. Lathwal, A., Kumar, R., Arora, C., & Raghava, G. P. S. (2020). Identification of prognostic biomarkers for major subtypes of non-small-cell lung cancer using genomic and clinical data. Journal of Cancer Research and Clinical Oncology, 146(11), 2743–2752.

7. Lathwal, A., & Raghava, G. P. S. (2020). In-silico identification of biomarkers and vaccine candidates for advancement of lung cancer therapeutics. IIIT-Delhi.

8. Kaur, H., Dhall, A., Kumar, R., & Raghava, G. P. S. (2020). Identification of platform-independent diagnostic biomarker panel for hepatocellular carcinoma using large-scale transcriptomics data. Frontiers in Genetics, 10, 1306.

9. Yang, M., Petralia, F., Li, Z., Li, H., Ma, W., Song, X., Kim, S., Lee, H., Yu, H., Lee, B., & others. (2020). Community Assessment of the Predictability of Cancer Protein and Phosphoprotein Levels from Genomics and Transcriptomics. Cell Systems, 11(2), 186–195.

10. Kaur, H., Bhalla, S., Garg, D., Mehta, N., & Raghava, G. P. S. (2020). Analysis and prediction of cholangiocarcinoma from transcriptomic profile of patients. Journal of Hepatology, 73(1), A023.

11. Patiyal, S., Agrawal, P., Kumar, V., Dhall, A., Kumar, R., Mishra, G., & Raghava, G. P. S. (2020). NAGbinder: An approach for identifying N-acetylglucosamine interacting residues of a protein from its primary sequence. Protein Science, 29(1), 201–210.

12. Bhalla, S., Kaur, H., Kaur, R., Sharma, S., & Raghava, G. P. S. (2020). Expression based biomarkers and models to classify early and late-stage samples of Papillary Thyroid Carcinoma. PloS One, 15(4), e0231629.

13. Lathwal, A., Kumar, R., & Raghava, G. P. S. (2020). OvirusTdb: A database of oncolytic viruses for the advancement of therapeutics in cancer. Virology, 548, 109–116.

14. Arora, C., Kaur, D., Lathwal, A., & Raghava, G. P. S. (2020). Risk prediction in cutaneous melanoma patients from their clinico-pathological features: superiority of clinical data over gene expression data. Heliyon, 6, e04811.

15. Kaur, H., Bhalla, S., Kaur, D., & Raghava, G. P. S. (2020). CancerLivER: a database of liver cancer gene expression resources and biomarkers. Database : the journal of biological databases and curation, baaa012.

16. Sharma, N., Patiyal, S., Dhall, A., Pande, A., Arora, C., & Raghava, G. P. S. (2020). AlgPred 2.0: an improved method for predicting allergenic proteins and mapping of IgE epitopes. Briefings in Bioinformatics, bbaa294.

17. Kumar, V., Kumar, R., Agrawal, P., Patiyal, S., & Raghava, G. P. S. (2020). A Method for Predicting Hemolytic Potency of Chemically Modified Peptides From Its Structure. Frontiers in Pharmacology, 11, 54.

18. Lathwal, A., Kumar, R., & Raghava, G. P. S. (2020). Computer-aided designing of oncolytic viruses for overcoming translational challenges of cancer immunotherapy. Drug discovery today, 25(7), 1198–1205.

19. Mason, M. J., Schinke, C., Eng, C. L. P., Towfic, F., Gruber, F., Dervan, A., White, B. S., Pratapa, A., Guan, Y., Chen, H., & others. (2020). Multiple Myeloma DREAM Challenge reveals epigenetic regulator PHF19 as marker of aggressive disease. Leukemia, 34(7), 1866–1874.

20. Usmani, S. S., & Raghava, G. P. S. (2020). Potential Challenges for Coronavirus (SARS-CoV-2) Vaccines Under Trial. Frontiers in Immunology, 11, 2562.

21. Dhall, A., Patiyal, S., Sharma, N., Usmani, S. S., & Raghava, G. P. S. (2020). Computer-aided prediction and design of IL-6 inducing peptides: IL-6 plays a crucial role in COVID-19. Briefings in Bioinformatics, bbaa259.

22. Kaur, D., Arora, C., & Raghava, G. P. S. (2020). A Hybrid Model for Predicting Pattern Recognition Receptors Using Evolutionary Information. Frontiers in Immunology, 11, 71.

23. Agrawal, P., Bhagat, D., Mahalwal, M., Sharma, N., & Raghava, G. P. S. (2020). AntiCP 2.0: an updated model for predicting anticancer peptides. Briefings in Bioinformatics, bbaa153.

24. Dhall, A., Patiyal, S., Kaur, H., Bhalla, S., Arora, C., & Raghava, G. P. S. (2020). Computing Skin Cutaneous Melanoma Outcome From the HLA-Alleles and Clinical Characteristics. Frontiers in Genetics, 11.

25. Agrawal, P., Kumar, S., Singh, A., Raghava, G. P. S., & Singh, I. K. (2019). NeuroPIpred: a tool to predict, design and scan insect neuropeptides. Scientific Reports, 9(1).

26. Agrawal, P., Patiyal, S., Kumar, R., Kumar, V., Singh, H., Raghav, P. K., & Raghava, G. P. S. (2019). ccPDB 2.0: an updated version of datasets created and compiled from Protein Data Bank. Database: the journal of biological databases and curation, bay142.

27. Agrawal, P., Singh, H., Srivastava, H. K., Singh, S., Kishore, G., & Raghava, G. P. S. (2019). Benchmarking of different molecular docking methods for protein-peptide docking. BMC Bioinformatics, 19(13), 105–124.

28. Ahmad, S., Gromiha, M. M., Raghava, G. P. S., Schönbach, C., & Ranganathan, S. (2019). APBioNet’s annual International Conference on Bioinformatics (InCoB) returns to India in 2018. BioMed Central.

29. Akhter, S., Kaur, H., Agrawal, P., & Raghava, G. P. S. (2019). RareLSD: a manually curated database of lysosomal enzymes associated with rare diseases. Database: the journal of biological databases and curation, baz112.

30. Bhalla, S., Kaur, H., Dhall, A., & Raghava, G. P. S. (2019). Prediction and analysis of skin cancer progression using genomics profiles of patients. Scientific Reports, 9(1), 1–16.

31. Brown, P., Tan, A.-C., El-Esawi, M. A., Liehr, T., Blanck, O., Gladue, D. P., Almeida, G. M. F., Cernava, T., Sorzano, C. O., Yeung, A. W. K., & others. (2019). Large expert-curated database for benchmarking document similarity detection in biomedical literature search. Database : the journal of biological databases and curation, baz085.

32. Kaur, D., Patiyal, S., Sharma, N., Usmani, S. S., & Raghava, G. P. S. (2019). PRRDB 2.0: A comprehensive database of pattern-recognition receptors and their ligands. Database : the journal of biological databases and curation, baz076.

33. Kaur, H., Bhalla, S., & Raghava, G. P. S. (2019). Classification of early and late stage liver hepatocellular carcinoma patients from their genomics and epigenomics profiles. PloS One, 14(9), e0221476.

34. Kumar, R., Nagpal, G., Kumar, V., Usmani, S. S., Agrawal, P., & Raghava, G. P. S. (2019). HumCFS: a database of fragile sites in human chromosomes. BMC Genomics, 19(9), 1–8.

35. Kumar, R., Patiyal, S., Kumar, V., Nagpal, G., & Raghava, G. P. S. (2019). In Silico Analysis of Gene Expression Change Associated with Copy Number of Enhancers in Pancreatic Adenocarcinoma. International Journal of Molecular Sciences, 20(14), 3582.

36. Lathwal, A., Arora, C., & Raghava, G. P. S. (2019). Prediction of risk scores for colorectal cancer patients from the concentration of proteins involved in mitochondrial apoptotic pathway. PloS One, 14(9), e0217527.

37. Raghav, P. K., Kumar, R., Kumar, V., & Raghava, G. P. S. (2019). Docking-based approach for identification of mutations that disrupt binding between Bcl-2 and Bax proteins: Inducing apoptosis in cancer cells. Molecular Genetics & Genomic Medicine, 7(11), e910.

38. Agrawal, P., Raghav, P. K., Bhalla, S., Sharma, N., & Raghava, G. P. S. (2018). Overview of free software developed for designing drugs based on protein-small molecules interaction. Current Topics in Medicinal Chemistry.

39. Agrawal, P., Bhalla, S., Chaudhary, K., Kumar, R., Sharma, M., & Raghava, G. P. S. (2018). In silico approach for prediction of antifungal peptides. Frontiers in Microbiology, 9, 323.

40. Agrawal, P., & Raghava, G. P. S. (2018). Prediction of Antimicrobial Potential of a Chemically Modified Peptide from its Tertiary Structure. Frontiers in Microbiology, 9, 2551.

41. Kumar, R., Kaur, R., Bhondekar, A. P., & Raghava, G. P. S. (2018). Human Opinion Inspired Feature Selection Strategy for Predicting the Pleasantness of a Molecule. In Advanced Computational and Communication Paradigms (pp. 197–205). Springer.

42. Kumar, V., Agrawal, P., Kumar, R., Bhalla, S., Usmani, S. S., Varshney, G. C., & Raghava, G. P. S. (2018). Prediction of cell-penetrating potential of modified peptides containing natural and chemically modified residues. Frontiers in Microbiology, 9, 725.

43. Mathur, D., Mehta, A., Firmal, P., Bedi, G., Sood, C., Gautam, A., & Raghava, G. P. S. (2018). TopicalPdb: A database of topically delivered peptides. Plos One, 13(2), e0190134.

44. Mathur, D., Singh, S., Mehta, A., Agrawal, P., & Raghava, G. P. S. (2018). In silico approaches for predicting the half-life of natural and modified peptides in blood. PloS One, 13(6), e0196829.

45. Nagpal, G., Chaudhary, K., Agrawal, P., & Raghava, G. P. S. (2018). Computer-aided prediction of antigen presenting cell modulators for designing peptide-based vaccine adjuvants. Journal of Translational Medicine, 16(1).

46. Nagpal, G., Usmani, S. S., & Raghava, G. P. S. (2018). A web resource for designing subunit vaccine against major pathogenic species of bacteria. Frontiers in Immunology, 9, 2280.

47. Usmani, S. S., Bhalla, S., & Raghava, G. P. S. (2018). Prediction of antitubercular peptides from sequence information using ensemble classifier and hybrid features. Frontiers in Pharmacology, 9, 954.

48. Usmani, S. S., Kumar, R., Bhalla, S., Kumar, V., & Raghava, G. P. S. (2018). In Silico Tools and Databases for Designing Peptide-Based Vaccine and Drugs. In Advances in Protein Chemistry and Structural Biology (Vol. 112, pp. 221–263). Academic Press Inc.

49. Usmani, S. S., Kumar, R., Kumar, V., Singh, S., & Raghava, G. P. S. (2018). AntiTbPdb: a knowledgebase of anti-tubercular peptides. Database : the journal of biological databases and curation, bay025.

50. Baindara, P., Gautam, A., Raghava, G. P. S., & Korpole, S. (2017). Anticancer properties of a defensin like class IId bacteriocin Laterosporulin10. Scientific Reports, 7(1), 1–9.

51. Bhalla, S., Chaudhary, K., Kumar, R., Sehgal, M., Kaur, H., Sharma, S., & Raghava, G. P. S. (2017). Gene expression-based biomarkers for discriminating early and late stage of clear cell renal cancer. Scientific Reports, 7, 44997.

52. Bhalla, S., Sharma, S., & Raghava, G. P. S. (2017). Challenges in Prediction of different Cancer Stages using Gene Expression Profile of Cancer Patients. Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, 602.

53. Bhalla, S., Verma, R., Kaur, H., Kumar, R., Usmani, S. S., Sharma, S., & Raghava, G. P. S. (2017). CancerPDF: A repository of cancer-associated peptidome found in human biofluids. Scientific Reports, 7(1), 1511.

54. Dhanda, S. K., Usmani, S. S., Agrawal, P., Nagpal, G., Gautam, A., & Raghava, G. P. S. (2017). Novel in silico tools for designing peptide-based subunit vaccines and immunotherapeutics. Briefings in Bioinformatics, 18(3), 467–478.

55. Gaur, A., Bhardwaj, A., Sharma, A., John, L., Vivek, Mr., Tripathi, N., Bharatam, P., Kumar, R., Janardhan, S., Mori, A., & others. (2017). Assessing therapeutic potential of molecules: molecular property diagnostic suite for tuberculosis (MPDS^TB).

56. Keller, A., Gerkin, R. C., Guan, Y., Dhurandhar, A., Turu, G., Szalai, B., Mainland, J. D., Ihara, Y., Yu, C. W., Wolfinger, R., & others. (2017). Predicting human olfactory perception from chemical features of odor molecules. Science, eaal2014.

57. Nagpal, G., Chaudhary, K., Dhanda, S. K., & Raghava, G. P. S. (2017). Computational Prediction of the Immunomodulatory Potential of RNA Sequences. In RNA Nanostructures (pp. 75–90). Humana Press, New York, NY.

58. Nagpal, G., Usmani, S. S., Dhanda, S. K., Kaur, H., Singh, S., Sharma, M., & Raghava, G. P. S. (2017). Computer-aided designing of immunosuppressive peptides based on IL-10 inducing potential. Scientific Reports, 7, 42851.

59. Pahil, S., Taneja, N., Ansari, H. R., & Raghava, G. P. S. (2017). In silico analysis to identify vaccine candidates common to multiple serotypes of Shigella and evaluation of their immunogenicity. PloS One, 12(8), e0180505.

60. Usmani, S. S., Bedi, G., Samuel, J. S., Singh, S., Kalra, S., Kumar, P., Ahuja, A. A., Sharma, M., Gautam, A., & Raghava, G. P. S. (2017). THPdb: Database of FDA-approved peptide and protein therapeutics. PLoS ONE, 12(7).

61. Agrawal, P., Bhalla, S., Usmani, S. S., Singh, S., Chaudhary, K., Raghava, G. P. S., & Gautam, A. (2016). CPPsite 2.0: a repository of experimentally validated cell-penetrating peptides. Nucleic Acids Research, 44(D1), D1098--D1103.

62. Chaudhary, K., Kumar, R., Singh, S., Tuknait, A., Gautam, A., Mathur, D., Anand, P., Varshney, G. C., & Raghava, G. P. S. (2016). A Web Server and Mobile App for Computing Hemolytic Potency of Peptides. Scientific Reports, 6, 22843.

63. Chaudhary, K., Nagpal, G., Dhanda, S. K., & Raghava, G. P. S. (2016). Prediction of Immunomodulatory potential of an RNA sequence for designing non-toxic siRNAs and RNA-based vaccine adjuvants. Scientific Reports, 6, 20678.

64. Dhanda, S. K., Chaudhary, K., Gupta, S., Brahmachari, S. K., & Raghava, G. P. S. (2016). A web-based resource for designing therapeutics against Ebola Virus. Scientific Reports, 6, 24782.

65. Dhanda, S. K., Vir, P., Singla, D., Gupta, S., Kumar, S., & Raghava, G. P. S. (2016). A web-based platform for designing vaccines against existing and emerging strains of Mycobacterium tuberculosis. PloS One, 11(4), e0153771.

66. Gautam, A., Chaudhary, K., Kumar, R., Gupta, S., Singh, H., & Raghava, G. P. S. (2016). Managing Drug Resistance in Cancer: Role of Cancer Informatics. Cancer Drug Resistance: Overviews and Methods, 299–312.

67. Gautam, A., Nanda, J. S., Samuel, J. S., Kumari, M., Priyanka, P., Bedi, G., Nath, S. K., Mittal, G., Khatri, N., & Raghava, G. P. S. (2016). Topical Delivery of Protein and Peptide Using Novel Cell Penetrating Peptide IMT-P8. Scientific Reports, 6, 26278.

68. Gupta, A. K., Kaur, K., Rajput, A., Dhanda, S. K., Sehgal, M., Khan, M. S., Monga, I., Dar, S. A., Singh, S., Nagpal, G., & others. (2016). ZikaVR: An Integrated Zika Virus Resource for Genomics, Proteomics, Phylogenetic and Therapeutic Analysis. Scientific Reports, 6, 32713.

69. Gupta, S., Chaudhary, K., Dhanda, S. K., Kumar, R., Kumar, S., Sehgal, M., Nagpal, G., & Raghava, G. P. S. (2016). A platform for designing genome-based personalized immunotherapy or vaccine against cancer. PloS One, 11(11), e0166372.

70. Gupta, S., Chaudhary, K., Kumar, R., Gautam, A., Nanda, J. S., Dhanda, S. K., Brahmachari, S. K., & Raghava, G. P. S. (2016). Prioritization of anticancer drugs against a cancer using genomic features of cancer cells: A step towards personalized medicine. Scientific Reports, 6, 23857.

71. Jaiswal, S., Dhanda, S. K., Iquebal, M. A., Arora, V., Shah, T. M., Angadi, U. B., Joshi, C. G., Raghava, G. P. S., Rai, A., & Kumar, D. (2016). BIS-CATTLE: A Web Server for Breed Identification using Microsatellite DNA Markers.

72. Kumar, Rahul, & Raghava, G. P. S. (2016). ApoCanD: Database of human apoptotic proteins in the context of cancer. Scientific Reports, 6, 20797.

73. Kumar, Ritesh, Kaur, R., Bhondekar, A. P., & Raghava, G. P. S. (2016). Smell and language: datacentric approach to predicting smell of a molecule. Journal of Digital Olfaction Society, 4(1).

74. Mathur, D., Prakash, S., Anand, P., Kaur, H., Agrawal, P., Mehta, A., Kumar, R., Singh, S., & Raghava, G. P. S. (2016). PEPlife: A Repository of the Half-life of Peptides. Scientific Reports, 6, 36617.

75. Nanda, J. S., Kumar, R., & Raghava, G. P. S. (2016). dbEM: A database of epigenetic modifiers curated from cancerous and normal genomes. Scientific Reports, 6(1), 1–6.

76. Nupur, L. N. U., Vats, A., Dhanda, S. K., Raghava, G. P. S., Pinnaka, A. K., & Kumar, A. (2016). ProCarDB: a database of bacterial carotenoids. BMC Microbiology, 16(1), 1–8.

77. Randhawa, H. K., Gautam, A., Sharma, M., Bhatia, R., Varshney, G. C., Raghava, G. P. S., & Nandanwar, H. (2016). Cell-penetrating peptide and antibiotic combination therapy: a potential alternative to combat drug resistance in methicillin-resistant Staphylococcus aureus. Applied Microbiology and Biotechnology, 100(9), 4073–4083.

78. Singh, H., Kumar, R., Singh, S., Chaudhary, K., Gautam, A., & Raghava, G. P. S. (2016). Prediction of anticancer molecules using hybrid model developed on molecules screened against NCI-60 cancer cell lines. BMC Cancer, 16(1).

79. Singh, H., & Raghava, G. P. S. (2016). BLAST-based structural annotation of protein residues using Protein Data Bank. Biology Direct, 11(1), 1–13.

80. Singh, H., Srivastava, H. K., & Raghava, G. P. S. (2016). A web server for analysis, comparison and prediction of protein ligand binding sites. Biology Direct, 11(1), 14.

81. Singh, S., Chaudhary, K., Dhanda, S. K., Bhalla, S., Usmani, S. S., Gautam, A., Tuknait, A., Agrawal, P., Mathur, D., & Raghava, G. P. S. (2016). SATPdb: a database of structurally annotated therapeutic peptides. Nucleic Acids Research, 44(D1), D1119--D1126.

82. Bhatia, R., Gautam, A., Gautam, S. K., Mehta, D., Kumar, V., Raghava, G. P. S., & Varshney, G. C. (2015). Assessment of SYBR Green I Dye-Based Fluorescence Assay for Screening Antimalarial Activity of Cationic Peptides and DNA Intercalating Agents. Antimicrobial Agents and Chemotherapy, 59(5), 2886–2889.

83. Dhar, J., Chakrabarti, P., Saini, H., Raghava, G. P. S., & Kishore, R. (2015). ω-Turn: A novel β-turn mimic in globular proteins stabilized by main-chain to side-chain C H···O interaction. Proteins: Structure, Function, and Bioinformatics, 83(2), 203–214.

84. Gautam, A., Chaudhary, K., Kumar, R., & Raghava, G. P. S. (2015). Computer-aided virtual screening and designing of cell-penetrating peptides. In Cell-Penetrating Peptides (pp. 59–69). Humana Press, New York, NY.

85. Gautam, A., Sharma, M., Vir, P., Chaudhary, K., Kapoor, P., Kumar, R., Nath, S. K., & Raghava, G. P. S. (2015). Identification and characterization of novel protein-derived arginine-rich cell-penetrating peptides. European Journal of Pharmaceutics and Biopharmaceutics, 89, 93–106.

86. Gupta, S., Kapoor, P., Chaudhary, K., Gautam, A., Kumar, R., & Raghava, G. P. S. (2015). Peptide Toxicity Prediction. In Computational Peptidology (pp. 143–157). Springer New York.

87. Kumar, Rahul, Singh Chauhan, J., & Pal Singh Raghava, G. (2015). In Silico Designing and Screening of Antagonists against Cancer Drug Target XIAP. Current Cancer Drug Targets, 15(9), 836–846.

88. Kumar, Ravi, Chaudhary, K., Chauhan, J. S., Nagpal, G., Kumar, R., Sharma, M., & Raghava, G. P. S. (2015). An in silico platform for predicting, screening and designing of antihypertensive peptides. Scientific Reports, 5(1), 1–10.

89. Kumar, Ravi, Chaudhary, K., Sharma, M., Nagpal, G., Chauhan, J. S., Singh, S., Gautam, A., & Raghava, G. P. S. (2015). AHTPDB: a comprehensive platform for analysis and presentation of antihypertensive peptides. Nucleic Acids Research, 43(D1), D956--D962.

90. Nagpal, G., Gupta, S., Chaudhary, K., Dhanda, S. K., Prakash, S., & Raghava, G. P. S. (2015). VaccineDA: Prediction, design and genome-wide screening of oligodeoxynucleotide-based vaccine adjuvants. Scientific Reports, 5(1), 1–9.

91. Panwar, B., & Raghava, G. P. S. (2015). Identification of protein-interacting nucleotides in a RNA sequence using composition profile of tri-nucleotides. Genomics, 105(4), 197–203.

92. Singh, H., Gupta, S., Gautam, A., & Raghava, G. P. S. (2015). Designing B-Cell Epitopes for Immunotherapy and Subunit Vaccines. Peptide Antibodies: Methods and Protocols, 327–340.

93. Singh, H., Singh, S., & Raghava, G. P. S. (2015). In silico platform for predicting and initiating β-turns in a protein at desired locations. Proteins: Structure, Function and Bioinformatics, 83(5), 910–921.

94. Singh, H., Singh, S., Singla, D., Agarwal, S. M., & Raghava, G. P. S. (2015). QSAR based model for discriminating EGFR inhibitors and non-inhibitors using Random forest. Biology Direct, 10(1), 10.

95. Singh, S., Singh, H., Tuknait, A., Chaudhary, K., Singh, B., Kumaran, S., & Raghava, G. P. S. (2015). PEPstrMOD: structure prediction of peptides containing natural, non-natural and modified residues. Biology Direct, 10(1), 1–19.

96. Tyagi, A., Tuknait, A., Anand, P., Gupta, S., Sharma, M., Mathur, D., Joshi, A., Singh, S., Gautam, A., & Raghava, G. P. S. (2015). CancerPPD: a database of anticancer peptides and proteins. Nucleic Acids Research, 43(D1), D837--D843.

97. Ahmad, S., Gupta, S., Kumar, R., Varshney, G. C., & Raghava, G. P. S. (2014). Herceptin resistance database for understanding mechanism of resistance in breast cancer patients. Scientific Reports, 4, 4483.

98. Chauhan, J. S., Dhanda, S. K., Singla, D., Agarwal, S. M., Raghava, G. P. S., Consortium, O. S. D. D., & others. (2014). QSAR-Based Models for Designing Quinazoline/Imidazothiazoles/Pyrazolopyrimidines Based Inhibitors against Wild and Mutant EGFR. PLOS ONE, 9(7), e101079.

99. Gautam, A., Kapoor, P., Chaudhary, K., Kumar, R., Raghava, G. P. S., Consortium, S. D. D., & others. (2014). Tumor Homing Peptides as Molecular Probes for Cancer Therapeutics, Diagnostics and Theranostics. Current Medicinal Chemistry, 21(21), 2367–2391.

100. Kumar, R., Chaudhary, K., Singla, D., Gautam, A., & Raghava, G. P. S. (2014). Designing of promiscuous inhibitors against pancreatic cancer cell lines. Scientific Reports, 4, 4668.

101. Mehta, D., Anand, P., Kumar, V., Joshi, A., Mathur, D., Singh, S., Tuknait, A., Chaudhary, K., Gautam, S. K., Gautam, A., & others. (2014). ParaPep: a web resource for experimentally validated antiparasitic peptide sequences and their structures. Database,bau051.

102. Mishra, N. K., Singla, D., Agarwal, S., & Raghava, G. P. S. (2014). ToxiPred: A Server for Prediction of Aqueous Toxicity of Small Chemical Molecules in T. Pyriformis. Journal of Translational Toxicology, 1(1), 21–27.

103. Nagpal, G., Sharma, M., Kumar, S., Chaudhary, K., Gupta, S., Gautam, A., & Raghava, G. P. S. (2014). PCMdb: pancreatic cancer methylation database. Scientific Reports, 4, 4197.

104. Panwar, B., Arora, A., & Raghava, G. P. S. (2014). Prediction and classification of ncRNAs using structural information. BMC Genomics, 15(1), 127.

105. Panwar, B., & Raghava, G. P. S. (2014). Prediction of uridine modifications in tRNA sequences. BMC Bioinformatics, 15(1), 326.

106. S Yadav, I., Singh, H., Khan, I., Chaudhury, A., Raghava, G. P. S., M Agarwal, S., & others. (2014). EGFRIndb: Epidermal Growth Factor Receptor Inhibitor Database. Anti-Cancer Agents in Medicinal Chemistry (Formerly Current Medicinal Chemistry-Anti-Cancer Agents), 14(7), 928–935.

107. Sharma, A., Singla, D., Rashid, M., & Raghava, G. P. (2014). Designing of peptides with desired half-life in intestine-like environment. BMC Bioinformatics, 15(1), 282.

108. Singh, H., Singh, S., & Raghava, G. P. S. (2014). Evaluation of Protein Dihedral Angle Prediction Methods. PloS One, 9(8), e105667.

109. Ahmed, F., Kaundal, R., & Raghava, G. P. S. (2013). PHDcleav: a SVM based method for predicting human Dicer cleavage sites using sequence and secondary structure of miRNA precursors. BMC Bioinformatics, 14(Suppl 14), S9.

110. Ansari, H. R., Flower, D. R., & Raghava, G. (2013). Vaccine Antigen Databases. Encyclopedia of Systems Biology, 2331–2335.

111. Ansari, H. R., & Raghava, G. P. S. (2013). In Silico Models for B-Cell Epitope Recognition and Signaling. In In Silico Models for Drug Discovery (pp. 129–138). Humana Press.

112. Bala, M., Kumar, S., Raghava, G. P. S., & Mayilraj, S. (2013). Draft genome sequence of Rhodococcus qingshengii strain BKS 20-40. Genome Announcements, 1(2), e00128--13.

113. Bala, M., Kumar, S., Raghava, G. P. S., & Mayilraj, S. (2013). Draft genome sequence of Rhodococcus ruber strain BKS 20-38. Genome Announcements, 1(2), e00139--13.

114. Bhartiya, D., Pal, K., Ghosh, S., Kapoor, S., Jalali, S., Panwar, B., Jain, S., Sati, S., Sengupta, S., Sachidanandan, C., & others. (2013). lncRNome: a comprehensive knowledgebase of human long noncoding RNAs. Database, bat034.

115. Chauhan, J. S., Rao, A., & Raghava, G. P. S. (2013). In silico platform for prediction of N-, O-and C-glycosites in eukaryotic protein sequences. PloS One, 8(6), e67008.

116. Dhanda, S. K., Gupta, S., Vir, P., & Raghava, G. P. S. (2013). Prediction of IL4 inducing peptides. Clinical and Developmental Immunology, 2013.

117. Dhanda, S. K., Singla, D., Mondal, A. K., & Raghava, G. P. S. (2013). DrugMint: a webserver for predicting and designing of drug-like molecules. Biology Direct, 8(1), 1–12.

118. Gautam, A., Chaudhary, K., Kumar, R., Sharma, A., Kapoor, P., Tyagi, A., & Raghava, G. P. S. (2013). In silico approaches for designing highly effective cell penetrating peptides. Journal of Translational Medicine, 11(1).

119. Gautam, A., Chaudhary, K., Singh, S., Joshi, A., Anand, P., Tuknait, A., Mathur, D., Varshney, G. C., & Raghava, G. P. S. (2013). Hemolytik: a database of experimentally determined hemolytic and non-hemolytic peptides. Nucleic Acids Research, gkt1008.

120. Gupta, S., Ansari, H. R., Gautam, A., Raghava, G. P., Consortium, O. S. D. D., & others. (2013). Identification of B-cell epitopes in an antigen for inducing specific class of antibodies. Biology Direct, 8(1), 27.

121. Gupta, S., Kapoor, P., Chaudhary, K., Gautam, A., Kumar, R., Raghava, G. P. S., Consortium, O. S. D. D., & others. (2013). In Silico Approach for Predicting Toxicity of Peptides and Proteins. PloS One, 8(9), e73957.

122. Iquebal, M. A., Dhanda, S. K., Arora, V., Dixit, S. P., Raghava, G. P. S., Rai, A., Kumar, D., & others. (2013). Development of a model webserver for breed identification using microsatellite DNA marker. BMC Genetics, 14(1), 118.

123. Kaur, N., Kumar, S., Bala, M., Raghava, G. P. S., & Mayilraj, S. (2013). Draft genome sequence of Amycolatopsis decaplanina strain DSM 44594T. Genome Announcements, 1(2), e00138--13.

124. Kumar, Rahul, Chaudhary, K., Gupta, S., Singh, H., Kumar, S., Gautam, A., Kapoor, P., & Raghava, G. P. S. (2013). CancerDR: cancer drug resistance database. Scientific Reports, 3(1), 1–6.

125. Kumar, Ravi, Raghava, G. P. S., & Abrams, W. R. (2013). Hybrid approach for predicting coreceptor used by HIV-1 from its V3 loop amino acid sequence. PloS One, 8(4).

126. Kumar, S, Kaur, C., Kimura, K., Takeo, M., Raghava, G. P., & Mayilraj, S. (2013). Draft genome sequence of the type species of the genus Citrobacter, Citrobacter freundii MTCC 1658. Genome Announc 1 (1): e00120-12.

127. Kumar, Shailesh, Bala, M., Raghava, G. P. S., & Mayilraj, S. (2013). Draft genome sequence of Rhodococcus triatomae strain BKS 15-14. Genome Announcements, 1(2), e00129--13.

128. Kumar, Shailesh, Kaur, C., Kimura, K., Takeo, M., Raghava, G. P. S., & Mayilraj, S. (2013). Draft genome sequence of the type species of the genus Citrobacter, Citrobacter freundii MTCC 1658. Genome Announcements, 1(1), e00120--12.

129. Kumar, Shailesh, Kaur, N., Singh, N. K., Raghava, G. P. S., & Mayilraj, S. (2013). Draft genome sequence of Streptomyces gancidicus strain BKS 13-15. Genome Announcements, 1(2), e00150--13.

130. Kumar, Shailesh, Vikram, S., & Raghava, G. P. S. (2013). Genome annotation of Burkholderia sp. SJ98 with special focus on chemotaxis genes. PloS One, 8(8), e70624.

131. Mangal, M., Sagar, P., Singh, H., Raghava, G. P. S., & Agarwal, S. M. (2013). NPACT: naturally occurring plant-based anti-cancer compound-activity-target database. Nucleic Acids Research, 41(D1), D1124--D1129.

132. Monu, B., Shailesh, K., Raghava, G. P. S., Shanmugam, M., & others. (2013). Draft genome sequence of Rhodococcus ruber strain BKS 20-38. Genome Announcements, 1(2).

133. Panwar, B., Gupta, S., & Raghava, G. P. S. (2013). Prediction of vitamin interacting residues in a vitamin binding protein using evolutionary information. BMC Bioinformatics, 14(1), 44.

134. Sandeep Kumar, D., Pooja, V., & Gajendra, R. (2013). Designing of interferon-gamma inducing MHC class-II binders. Biology Direct, 8(1), 30.

135. Shailesh, K., Navjot, K., Singh, N. K., Raghava, G. P. S., Shanmugam, M., & others. (2013). Draft genome sequence of Streptomyces gancidicus strain BKS 13-15. Genome Announcements, 1(2).

136. Sharma, A., Kapoor, P., Gautam, A., Chaudhary, K., Kumar, R., Chauhan, J. S., Tyagi, A., & Raghava, G. P. S. (2013). Computational approach for designing tumor homing peptides. Scientific Reports, 3(1), 1–7.

137. Singh, H., Ansari, H. R., & Raghava, G. P. S. (2013). Improved method for linear B-cell epitope prediction using Antigen’s primary sequence. PloS One, 8(5), e62216.

138. Singh, N. K., Kumar, S., Raghava, G. P. S., & Mayilraj, S. (2013). Draft genome sequence of Acinetobacter baumannii strain MSP4-16. Genome Announcements, 1(2), e00137--13.

139. Singh, S. V., Kumar, N., Singh, S. N., Bhattacharya, T., Sohal, J. S., Singh, P. K., Singh, A. V., Singh, B., Chaubey, K. K., Gupta, S., & others. (2013). Genome sequence of the “Indian Bison Type” biotype of Mycobacterium avium subsp. paratuberculosis strain S5. Genome Announcements, 1(1), e00005--13.

140. Singla, D., Dhanda, S. K., Chauhan, J. S., Bhardwaj, A., Brahmachari, S. K., Raghava, G. P. S., & others. (2013). Open Source Software and Web Services for Designing Therapeutic Molecules. Current Topics in Medicinal Chemistry, 13(10), 1172–1191.

141. Singla, D., Tewari, R., Kumar, A., & Raghava, G. P. S. (2013). Designing of inhibitors against drug tolerant Mycobacterium tuberculosis (H37Rv). Chemistry Central Journal, 7(1), 49.

142. Tyagi, A., Kapoor, P., Kumar, R., Chaudhary, K., Gautam, A., & Raghava, G. P. S. (2013). In silico models for designing and discovering novel anticancer peptides. Scientific Reports, 3(1), 1–8.

143. Vikram, S., Kumar, S., Vaidya, B., Pinnaka, A. K., & Raghava, G. P. S. (2013). Draft genome sequence of the 2-chloro-4-nitrophenol-degrading bacterium Arthrobacter sp. strain SJCon. Genome Announcements, 1(2), e00058--13.

144. Vikram, S., Pandey, J., Kumar, S., & Raghava, G. P. S. (2013). Genes Involved in Degradation of para-Nitrophenol Are Differentially Arranged in Form of Non-Contiguous Gene Clusters in Burkholderia sp. strain SJ98. PloS One, 8(12), e84766.

145. Aithal, A., Sharma, A., Joshi, S., Raghava, G. P. S., & Varshney, G. C. (2012). PolysacDB: A Database of Microbial Polysaccharide Antigens and Their Antibodies. PloS One, 7(4), e34613.

146. Ansari, H. R., Flower, D. R., & Raghava, G. P. S. (2012). On the Development of Vaccine Antigen Databases: Progress, Opportunity, and Challenge. In Immunomic Discovery of Adjuvants and Candidate Subunit Vaccines(p. 117). Springer.

147. Bhat, A. H., Mondal, H., Chauhan, J. S., Raghava, G. P. S., Methi, A., & Rao, A. (2012). ProGlycProt: a repository of experimentally characterized prokaryotic glycoproteins. Nucleic Acids Research, 40(D1), D388--D393.

148. Chauhan, J. S., Bhat, A. H., Raghava, G. P. S., & Rao, A. (2012). GlycoPP: a webserver for prediction of N-and O-glycosites in prokaryotic protein sequences. PloS One, 7(7), e40155.

149. Gautam, A., Singh, H., Tyagi, A., Chaudhary, K., Kumar, R., Kapoor, P., & Raghava, G. P. S. (2012). CPPsite: a curated database of cell penetrating peptides. Database, bas015.

150. Kapoor, P., Singh, H., Gautam, A., Chaudhary, K., Kumar, R., & Raghava, G. P. S. (2012). TumorHoPe: a database of tumor homing peptides. PLoS One, 7(4), e35187.

151. Kumar, S., Kushwaha, H., Bachhawat, A. K., Raghava, G. P. S., & Ganesan, K. (2012). Genome sequence of the oleaginous red yeast Rhodosporidium toruloides MTCC 457. Eukaryotic Cell, 11(8), 1083–1084.

152. Kumar, S., Randhawa, A., Ganesan, K., Raghava, G. P. S., & Mondal, A. K. (2012). Draft Genome Sequence of Salt-Tolerant Yeast Debaryomyces hansenii var. hansenii MTCC 234. Eukaryotic Cell, 11(7), 961–962.

153. Kumar, S., Subramanian, S., Raghava, G. P. S., & Pinnaka, A. K. (2012). Genome sequence of the marine bacterium Marinilabilia salmonicolor JCM 21150T. Journal of Bacteriology, 194(14), 3746.

154. Kumar, S., Vikram, S., & Raghava, G. P. S. (2012). Genome sequence of the nitroaromatic compound-degrading Bacterium Burkholderia sp. strain SJ98. Journal of Bacteriology, 194(12), 3286.

155. Kumar, S., Vikram, S., Subramanian, S., Raghava, G. P. S., & Pinnaka, A. K. (2012). Genome Sequence of the Halotolerant Bacterium Imtechella halotolerans K1T. Journal of Bacteriology, 194(14), 3731.

156. Raghava, G. P. S., Pinnaka, A. K., Kumar, S., Vikram, S., & Subramanian, S. (2012). Genome Sequence of the Halotolerant. J. Bacteriol, 194(14), 3731.

157. Singh, H., Chauhan, J. S., Gromiha, M. M., Raghava, G. P. S., & others. (2012). ccPDB: compilation and creation of data sets from Protein Data Bank. Nucleic Acids Research, 40(D1), D486--D489.

158. Vikram, S., Kumar, S., Subramanian, S., & Raghava, G. P. S. (2012). Draft genome sequence of the nitrophenol-degrading actinomycete Rhodococcus imtechensis RKJ300. Journal of Bacteriology, 194(13), 3543.

159. Vikram, S., Pandey, J., Bhalla, N., Pandey, G., Ghosh, A., Khan, F., Jain, R. K., & Raghava, G. P. S. (2012). Branching of the p-nitrophenol (PNP) degradation pathway in burkholderia sp. Strain SJ98: Evidences from genetic characterization of PNP gene cluster. AMB Express, 2(1), 1–10.

160. Agarwal, S., Kumar Mishra, N., Singh, H., & Raghava, G. P. S. (2011). Identification of mannose interacting residues using local composition. PloS One, 6(9), e24039_1--e24039_9.

161. Ahmed, F., & Raghava, G. P. S. (2011). Designing of Highly Effective Complementary and Mismatch siRNAs for Silencing a Gene. PLoS ONE, 6(8), e23443.

162. Bhardwaj, A, Scaria, V., Raghava, G. P., Lynn, A. M., Chandra, N., Banerjee, S., Raghunandanan, M. V, Pandey, V., Taneja, B., Yadav, J., & others. (2011). Open Source Drug Discovery C, Brahmachari SK. Open source drug discovery—a new paradigm of collaborative research in tuberculosis drug development. Tuberculosis, 91(5), 479–486.

163. Bhardwaj, Anshu, Scaria, V., Raghava, G. P. S., Lynn, A. M., Chandra, N., Banerjee, S., Raghunandanan, M. V, Pandey, V., Taneja, B., Yadav, J., & others. (2011). Open source drug discovery--A new paradigm of collaborative research in tuberculosis drug development. Tuberculosis, 91(5), 479–486.

164. Kumar, M., Gromiha, M. M., & Raghava, G. P. S. (2011). SVM based prediction of RNA-binding proteins using binding residues and evolutionary information. Journal of Molecular Recognition, 24(2), 303–313.

165. Kumar Mishra, N., Raghava, P. S., & others. (2011). Prediction of Specificity and Cross-Reactivity of Kinase Inhibitors. Letters in Drug Design &# 38; Discovery, 8(3), 223–228.

166. Kumar, R., Panwar, B., Chauhan, J. S., & Raghava, G. P. S. (2011). Analysis and prediction of cancerlectins using evolutionary and domain information. BMC Research Notes, 4(1), 237.

167. Panwar, B., & Raghava, G. P. S. (2011). Predicting sub-cellular localization of tRNA synthetases from their primary structures. Amino Acids, 1–11.

168. Singla, D., Anurag, M., Dash, D., & Raghava, G. P. S. (2011). A web server for predicting inhibitors against bacterial target GlmU protein. BMC Pharmacology, 11(1), 1–9.

169. Tyagi, A., Ahmed, F., Thakur, N., Sharma, A., Raghava, G. P. S., & Kumar, M. (2011). HIVsirDB: a database of HIV inhibiting siRNAs. PLoS One, 6(10), e25917_1--e25917_6.

170. Zhang, G. L., Ansari, H. R., Bradley, P., Cawley, G. C., Hertz, T., Hu, X., Jojic, N., Kim, Y., Kohlbacher, O., Lund, O., & others. (2011). Machine learning competition in immunology--Prediction of HLA class I binding peptides. Journal of Immunological Methods, 374(1), 1–4.

171. Agarwal, S. M., Raghav, D., Singh, H., & Raghava, G. P. S. (2010). CCDB: a curated database of genes involved in cervix cancer. Nucleic Acids Research, 39(suppl_1), D975--D979.

172. Anastas, P., Bejatolah, M.-K., Gajendra, P. S., & others. (2010). Bridging Innate and Adaptive Antitumor Immunity Targeting Glycans. Journal of Biomedicine and Biotechnology, 2010.

173. Ansari, H., Flower, D., & Raghava, G. (2010). AntigenDB. Nucleic Acids Research, 38(20103804).

174. Ansari, Hifzur R, & Raghava, G. P. S. (2010). Identification of NAD interacting residues in proteins. BMC Bioinformatics, 11(1), 160.

175. Ansari, Hifzur Rahman, Flower, D. R., & Raghava, G. P. S. (2010). AntigenDB: an immunoinformatics database of pathogen antigens. Nucleic Acids Research, 38(suppl_1), D847--D853.

176. Ansari, Hifzur Rahman, & Raghava, G. P. S. (2010). Identification of conformational B-cell Epitopes in an antigen from its primary sequence. Immunome Research, 6(1), 1–9.

177. Chauhan, J. S., Mishra, N. K., & Raghava, G. P. S. (2010). Prediction of GTP interacting residues, dipeptides and tripeptides in a protein from its evolutionary information. BMC Bioinformatics, 11(1), 301.

178. Garg, A., Tewari, R., & Raghava, G. P. S. (2010). KiDoQ: using docking based energy scores to develop ligand based model for predicting antibacterials. BMC Bioinformatics, 11(1), 125.

179. Garg, A., Tewari, R., & Raghava, G. P. S. (2010). Virtual screening of potential drug-like inhibitors against Lysine/DAP pathway of Mycobacterium tuberculosis. BMC Bioinformatics, 11(Suppl 1), S53.

180. Lata, S., Mishra, N. K., & Raghava, G. P. S. (2010). AntiBP2: improved version of antibacterial peptide prediction. BMC Bioinformatics, 11(Suppl 1), S19.

181. Mishra, N. K., Agarwal, S., & Raghava, G. P. S. (2010). Prediction of cytochrome P450 isoform responsible for metabolizing a drug molecule. BMC Pharmacology, 10(1), 1–9.

182. Mishra, N. K., & Raghava, G. P. S. (2010). Prediction of FAD interacting residues in a protein from its primary sequence using evolutionary information. BMC Bioinformatics, 11(Suppl 1), S48.

183. Panwar, B., & Raghava, G. P. S. (2010). Prediction and classification of aminoacyl tRNA synthetases using PROSITE domains. BMC Genomics, 11(1), 507.

184. Raghava, G., Garg, A., & Tewari, R. (2010). KiDoq A web server for predicting DHDPS inhibitors.

185. Rashid, M., Ramasamy, S., & Raghava, G. P. S. (2010). A Simple Approach for Predicting Protein-Protein Interactions. Current Protein and Peptide Science, 11(7), 589–600.

186. Singla, D., Sharma, A., Kaur, J., Panwar, B., & Raghava, G. P. S. (2010). BIAdb: a curated database of benzylisoquinoline alkaloids. BMC Pharmacology, 10(1), 1–8.

187. Verma, R., Varshney, G. C., & Raghava, G. P. S. (2010). Prediction of mitochondrial proteins of malaria parasite using split amino acid composition and PSSM profile. Amino Acids, 39(1), 101–110.

188. Ahmed, F., Ansari, H. R., & Raghava, G. P. S. (2009). Prediction of guide strand of microRNAs from its sequence and secondary structure. BMC Bioinformatics, 10(1), 105.

189. Ahmed, F., Kumar, M., & Raghava, G. P. S. (2009). Prediction of polyadenylation signals in human DNA sequences using nucleotide frequencies. In Silico Biology, 9(3), 135–148.

190. Arora, P. K., Kumar, M., Chauhan, A., Raghava, G. P. S., & Jain, R. K. (2009). OxDBase: a database of oxygenases involved in biodegradation. BMC Research Notes, 2(1), 67.

191. Chaudhary, N., Mahajan, L., Madan, T., Kumar, A., Raghava, G. P. S., Katti, S. B., Haq, W., & Sarma, P. U. (2009). Prophylactic and Therapeutic Potential of Asp f1 Epitopes in Na{\"\i}ve and Sensitized BALB/c Mice. Immune Network, 9(5), 179.

192. Chauhan, J. S., Mishra, N. K., & Raghava, G. P. S. (2009). Identification of ATP binding residues of a protein from its primary sequence. BMC Bioinformatics, 10(1), 434.

193. Kaundal, R., & Raghava, G. P. S. (2009). RSLpred: An integrative system for predicting subcellular localization of rice proteins combining compositional and evolutionary information. Proteomics, 9(9), 2324–2342.

194. Kumar, M., & Raghava, G. P. S. (2009). Prediction of nuclear proteins using SVM and HMM models. BMC Bioinformatics, 10(1), 22.

195. Lata, S., Bhasin, M., & Raghava, G. P. S. (2009). MHCBN 4.0: A database of MHC/TAP binding peptides and T-cell epitopes. BMC Research Notes, 2(1), 61.

196. Lata, S., & Raghava, G. P. S. (2009). Databases and Web-Based Tools for Innate Immunity. In Bioinformatics for Immunomics (pp. 67–76). Springer New York.

197. Lata, S., & Raghava, G. P. S. (2009). Prediction and classification of chemokines and their receptors. Protein Engineering Design and Selection, gzp016.

198. Raghava, G. P. S. (2009). Is citation a good criterion? In 2018-05-06].

199. Singla, D., Raghava, G. P., Kumar, M., Sharma, A., & Rashid, M. (2009). Hmrbase: a database of hormones and their receptors. BMC Genomics, 10(1).

200. Garg, A., & Raghava, G. P. S. (2008). A machine learning based method for the prediction of secretory proteins using amino acid composition, their order and similarity-search. In Silico Biology, 8(2), 129–140.

201. Garg, A., & Raghava, G. P. S. (2008). ESLpred2: improved method for predicting subcellular localization of eukaryotic proteins. BMC Bioinformatics, 9(1), 503.

202. Kalita, M. K., Nandal, U. K., Pattnaik, A., Sivalingam, A., Ramasamy, G., Kumar, M., Raghava, G. P. S., & Gupta, D. (2008). CyclinPred: a SVM-based method for predicting cyclin protein sequences. PloS One, 3(7), e2605_1--e2605_12.

203. Kumar, M., Gromiha, M. M., & Raghava, G. P. S. (2008). Prediction of RNA binding sites in a protein using SVM and PSSM profile. Proteins: Structure, Function, and Bioinformatics, 71(1), 189–194.

204. Kumar, M., Thakur, V., & Raghava, G. P. S. (2008). COPid: composition based protein identification. In Silico Biology, 8(2), 121–128.

205. Kush, A., & Raghava, G. P. S. (2008). AC2DGel: analysis and comparison of 2D gels. Journal of Proteomics & Bioinformatics, 1(1), 43–46.

206. Lata, S., & Raghava, G. P. S. (2008). CytoPred: a server for prediction and classification of cytokines. Protein Engineering, Design & Selection, 21(4), 279–282.

207. Lata, S., & Raghava, G. P. S. (2008). PRRDB: a comprehensive database of pattern-recognition receptors and their ligands. BMC Genomics, 9(1), 180.

208. Raghava Han JH, H. D. J. (2008). ECGpred: Correlation and prediction of gene expression from nucleotide sequence. The Open Bioinformatics Journal, 2, 64–67.

209. Sethi, D., Garg, A., & Raghava, G. P. S. (2008). DPROT: prediction of disordered proteins using evolutionary information. Amino Acids, 35(3), 599.

210. Verma, R., Tiwari, A., Kaur, S., Varshney, G. C., & Raghava, G. P. S. (2008). Identification of Proteins Secreted by Malaria Parasite into Erythrocyte using SVM and PSSM profiles. BMC Bioinformatics, 9(1), 201.

211. Vivona, S., Gardy, J. L., Ramachandran, S., Brinkman, F. S. L., Raghava, G. P. S., Flower, D. R., & Filippini, F. (2008). Computer-aided biotechnology: from immuno-informatics to reverse vaccinology. Trends in Biotechnology, 26(4), 190–200.

212. Bhasin, M., Lata, S., & Raghava, G. P. S. (2007). Searching and mapping of T-cell epitopes, MHC binders, and TAP binders. In Immunoinformatics (pp. 95–112). Humana Press.

213. Bhasin, M., Lata, S., & Raghava, G. P. S. (2007). TAPPred prediction of TAP-binding peptides in antigens. In Immunoinformatics (pp. 381–386). Humana Press.

214. Bhasin, M., & Raghava, G. P. S. (2007). A hybrid approach for predicting promiscuous MHC class I restricted T cell epitopes. Journal of Biosciences, 32(1), 31–42.

215. Greenbaum, J. A., Andersen, P. H., Blythe, M., Bui, H.-H., Cachau, R. E., Crowe, J., Davies, M., Kolaskar, A. S., Lund, O., Morrison, S., & others. (2007). Towards a consensus on datasets and evaluation metrics for developing B-cell epitope prediction tools. Journal of Molecular Recognition, 20(2), 75–82.

216. Kaur, H., Garg, A., & Raghava, G. P. S. (2007). PEPstr: a de novo method for tertiary structure prediction of small bioactive peptides. Protein and Peptide Letters, 14(7), 626–631.

217. Kumar, M., Gromiha, M. M., & Raghava, G. P. S. (2007). Identification of DNA-binding proteins using support vector machines and evolutionary profiles. BMC Bioinformatics, 8(1), 463.

218. Lata, S., Bhasin, M., & Raghava, G. P. S. (2007). Application of machine learning techniques in predicting MHC binders. In Immunoinformatics (pp. 201–215). Humana Press.

219. Lata, S., Sharma, B. K., & Raghava, G. P. S. (2007). Analysis and prediction of antibacterial peptides. BMC Bioinformatics, 8(1), 1–10.

220. Mishra, N. K., Kumar, M., & Raghava, G. P. S. (2007). Support vector machine based prediction of glutathione S-transferase proteins. Protein and Peptide Letters, 14(6), 575–580.

221. Muthukrishnan, S., Garg, A., & Raghava, G. P. S. (2007). Oxypred: prediction and classification of oxygen-binding proteins. Genomics, Proteomics & Bioinformatics, 5(3–4), 250–252.

222. Pashov, A., Monzavi-Karbassi, B., Raghava, G., & Kieber-Emmons, T. (2007). Peptide mimotopes as prototypic templates of broad-spectrum surrogates of carbohydrate antigens for cancer vaccination. Critical Reviews^TM in Immunology, 27(3).

223. Rashid, M., Saha, S., & Raghava, G. P. S. (2007). Support Vector Machine-based method for predicting subcellular localization of mycobacterial proteins using evolutionary information and motifs. BMC Bioinformatics, 8(1), 1–9.

224. Saha, S., & Raghava, G. P. S. (2007). BTXpred: prediction of bacterial toxins. In Silico Biology, 7(4–5), 405–412.

225. Saha, S., & Raghava, G. P. S. (2007). Predicting virulence factors of immunological interest. In Immunoinformatics (pp. 407–415). Humana Press.

226. Saha, S., & Raghava, G. P. S. (2007). Prediction methods for B-cell epitopes. In Immunoinformatics (pp. 387–394). Humana Press.

227. Saha, S., & Raghava, G. P. S. (2007). Prediction of neurotoxins based on their function and source. In Silico Biology, 7(4–5), 369–387.

228. Saha, S., & Raghava, G. P. S. (2007). Searching and mapping of B-cell epitopes in Bcipep database. In Methods Mol Biol. (Vol. 409, pp. 113–124). Humana Press.

229. Srivastava, S., Singh, M. K., Raghava, G. P. S., & Varshney, G. C. (2007). Searching haptens, carrier proteins, and anti-hapten antibodies. In Immunoinformatics (pp. 125–139). Humana Press.

230. Vidyasagar, M., Balakrishnan, N., & others. (2007). BioSuite: A comprehensive bioinformatics software package (A unique industry-academia collaboration). Current Science, 92(1), 29–38.

231. Bhasin, M., & Raghava, G. P. S. (2006). Computational Methods in Genome Research. In Applied Mycology and Biotechnology (Vol. 6, pp. 179–207). Elsevier.

232. Kaundal, R., Kapoor, A. S., & Raghava, G. P. S. (2006). Machine learning techniques in disease forecasting: a case study on rice blast prediction. BMC Bioinformatics, 7(1), 485.

233. Kaur, H., & Raghava, G. P. S. (2006). Prediction of Cα-H·O and Cα-H·π Interactions in Proteins Using Recurrent Neural Network. In Silico Biology, 6(1–2), 111–125.

234. Kim, J. K., Raghava, G. P. S., Bang, S.-Y., & Choi, S. (2006). Prediction of subcellular localization of proteins using pairwise sequence alignment and support vector machine. Pattern Recognition Letters, 27(9), 996–1001.

235. Kumar, M., Verma, R., & Raghava, G. P. S. (2006). Prediction of mitochondrial proteins using support vector machine and hidden Markov model. Journal of Biological Chemistry, 281(9), 5357–5363.

236. Raghava, G. P. S. (2006). MANGO: prediction of Genome Ontology (GO) class of a protein from its amino acid and dipeptide composition using nearest neighbor approach. CASP7: Proceedings of the 7th Meeting on the Critical Assessment of Techniques for Protein Structure Prediction, 26–30.

237. Raghava, G. P. S., & Barton, G. J. (2006). Quantification of the variation in percentage identity for protein sequence alignments. BMC Bioinformatics, 7(1), 415.

238. Saha, S., & Raghava, G. P. S. (2006). Prediction of continuous B-cell epitopes in an antigen using recurrent neural network. Proteins: Structure, Function, and Bioinformatics, 65(1), 40–48.

239. Saha, S., & Raghava, G. P. S. (2006). VICMpred: an SVM-based method for the prediction of functional proteins of Gram-negative bacteria using amino acid patterns and composition. Genomics, Proteomics & Bioinformatics, 4(1), 42–47.

240. Saha, S., & Raghava, G. P. S. (2006). AlgPred: Prediction of allergenic proteins and mapping of IgE epitopes. Nucleic Acids Research, 34(WEB. SERV. ISS.).

241. Saha, S., Zack, J., Singh, B., & Raghava, G. P. S. (2006). VGIchan: prediction and classification of voltage-gated ion channels. Genomics, Proteomics & Bioinformatics, 4(4), 253–258.

242. Singh, M. K., Srivastava, S., Raghava, G. P. S., & Varshney, G. C. (2006). HaptenDB: a comprehensive database of haptens, carrier proteins and anti-hapten antibodies. Bioinformatics, 22(2), 253–255.

243. Bhasin, M., Garg, A., & Raghava, G. P. S. (2005). PSLpred: prediction of subcellular localization of bacterial proteins. Bioinformatics, 21(10), 2522–2524.

244. Bhasin, M., & Raghava, G. P. S. (2005). GPCRsclass: a web tool for the classification of amine type of G-protein-coupled receptors. Nucleic Acids Research, 33(suppl_2), W143--W147.

245. Bhasin, M., & Raghava, G. P. S. (2005). Pcleavage: an SVM based method for prediction of constitutive proteasome and immunoproteasome cleavage sites in antigenic sequences. Nucleic Acids Research, 33(suppl_2), W202--W207.

246. Garg, A., Bhasin, M., & Raghava, G. P. S. (2005). Support vector machine-based method for subcellular localization of human proteins using amino acid compositions, their order, and similarity search. Journal of Biological Chemistry, 280(15), 14427–14432.

247. Garg, A., Kaur, H., & Raghava, G. P. S. (2005). Real value prediction of solvent accessibility in proteins using multiple sequence alignment and secondary structure. Proteins: Structure, Function, and Bioinformatics, 61(2), 318–324.

248. Genet, H. (2005). The Indian genome variation database (IGVdb): a project overview. Hum Genet, 1–11.

249. Issac, B., & Raghava, G. P. S. (2005). FASTA Servers for Sequence Similarity Search. In The Proteomics Protocols Handbook (pp. 503–525). Humana Press.

250. Kumar, M., Bhasin, M., Natt, N. K., & Raghava, G. P. S. (2005). BhairPred: prediction of β-hairpins in a protein from multiple alignment information using ANN and SVM techniques. Nucleic Acids Research, 33(suppl_2), W154--W159.

251. Raghava, G. P. S., & Han, J. H. (2005). Correlation and prediction of gene expression level from amino acid and dipeptide composition of its protein. BMC Bioinformatics, 6(1), 59.

252. Saha, S., Bhasin, M., & Raghava, G. P. S. (2005). Bcipep: a database of B-cell epitopes. BMC Genomics, 6(1), 1–7.

253. Bhasin, M., & Raghava, G. P. S. (2004). Analysis and prediction of affinity of TAP binding peptides using cascade SVM. Protein Science, 13(3), 596–607.

254. Bhasin, M., & Raghava, G. P. S. (2004). Classification of nuclear receptors based on amino acid composition and dipeptide composition. Journal of Biological Chemistry, 279(22), 23262–23266.

255. Bhasin, M., & Raghava, G. P. S. (2004). ESLpred: SVM-based method for subcellular localization of eukaryotic proteins using dipeptide composition and PSI-BLAST. Nucleic Acids Research, 32(suppl_2), W414--W419.

256. Bhasin, M., & Raghava, G. P. S. (2004). GPCRpred: an SVM-based method for prediction of families and subfamilies of G-protein coupled receptors. Nucleic Acids Research, 32(suppl_2), W383--W389.

257. Bhasin, M., & Raghava, G. P. S. (2004). SVM based method for predicting HLA-DRB1* 0401 binding peptides in an antigen sequence. Bioinformatics, 20(3), 421–423.

258. Bhasin, M., & Raghava, G. P. S. (2004). Prediction of CTL epitopes using QM, SVM and ANN techniques. Vaccine,22(23–24), 3195–3204.

259. Issac, B., & Raghava, G. P. S. (2004). EGPred: prediction of eukaryotic genes using ab initio methods after combining with sequence similarity approaches. Genome Research, 14(9), 1756–1766.

260. Kaur, H., & Raghava, G. P. S. (2004). A neural network method for prediction of β-turn types in proteins using evolutionary information. Bioinformatics, 20(16), 2751–2758.

261. Kaur, H., & Raghava, G. P. S. (2004). Prediction of α-turns in proteins using PSI-BLAST profiles and secondary structure information. Proteins: Structure, Function, and Bioinformatics, 55(1), 83–90.

262. Kaur, H., & Raghava, G. P. S. (2004). Prediction of β-turns in proteins from multiple alignment using neural network. Protein Science, 12(3), 627–634.

263. Kaur, H., & Raghava, G. P. S. (2004). Role of evolutionary information in prediction of aromatic-backbone NH interactions in proteins. FEBS Letters, 564(1–2), 47–57.

264. Natt, N. K., Kaur, H., & Raghava, G. P. S. (2004). Prediction of transmembrane regions of β-barrel proteins using ANN-and SVM-based methods. PROTEINS: Structure, Function, and Bioinformatics, 56(1), 11–18.

265. Saha, S., & Raghava, G. P. S. (2004). BcePred: prediction of continuous B-cell epitopes in antigenic sequences using physico-chemical properties. International Conference on Artificial Immune Systems, 197–204.

266. Sharma, D., Issac, B., Raghava, G. P. S., & Ramaswamy, R. (2004). Spectral Repeat Finder (SRF): identification of repetitive sequences using Fourier transformation. Bioinformatics, 20(9), 1405–1412.

267. Bhasin, M, Singh, H., & Raghava, G. (2003). MHCBN: A Comprehensive Database of MHC Binding and Non-Binding Peptides. Bioinformatics, 19(5), 665.

268. Bhasin, Manoj, & Raghava, G. P. S. (2003). Prediction of promiscuous and high-affinity mutated MHC binders. Hybridoma and Hybridomics, 22(4), 229–234.

269. Kaur, H., & Raghava, G. P. S. (2003). A neural-network based method for prediction of γ-turns in proteins from multiple sequence alignment. Protein Science, 12(5), 923–929.

270. Kaur, H., & Raghava, G. P. S. (2003). BTEVAL: A Server for Evaluation of β-Turn Prediction Methods. Journal of Bioinformatics and Computational Biology, 1(03), 495–504.

271. Raghava, G. (2003). MHCBench: Evaluation of MHC Binding Peptide Prediction Algorithms.

272. Raghava, G. P. S., Searle, S. M. J., Audley, P. C., Barber, J. D., & Barton, G. J. (2003). OXBench: a benchmark for evaluation of protein multiple sequence alignment accuracy. BMC Bioinformatics, 4(1), 47.

273. Sarin, J., Raghava, G. P. S., & Chakraborti, P. K. (2003). Intrinsic contributions of polar amino acid residues toward thermal stability of an ABC--ATPase of mesophilic origin. Protein Science, 12(9), 2118–2120.

274. Singh, H., & Raghava, G. P. S. (2003). ProPred1: Prediction of promiscuous MHC class-I binding sites. Bioinformatics, 19(8), 1009–1014.

275. Issac, B., & Raghava, G. P. S. (2002). GWFASTA: server for FASTA search in eukaryotic and microbial genomes. Biotechniques, 33(3), 548–556.

276. Issac, B., Singh, H., Kaur, H., & Raghava, G. P. S. (2002). Locating probable genes using Fourier transform approach. Bioinformatics, 18(1), 196–197.

277. Kaur, H., & Raghava, G. P. S. (2002). An evaluation of β-turn prediction methods. Bioinformatics, 18(11), 1508–1514.

278. Kaur, H., & Raghava, G. P. S. (2002). BetaTPred: prediction of β-TURNS in a protein using statistical algorithms. Bioinformatics, 18(3), 498–499.

279. Raghava, G. P. S. (2002). APSSP2: A combination method for protein secondary structure prediction based on neural network and example based learning. CASP5. A-132.

280. Shivaji, S., Nautiyal, C. S., Ganguli, B. N., Paul, A. K., Adholeya, A., Raghava, G. P. S., & Chakrabarti, T. (2002). Collection of data on microbial resources of India. In Current Science (Vol. 83, Issue 1, p. 9).

281. Singh, H, & Raghava, G. P. S. (2002). Matrix Optimization Technique for Predicting MHC binding Core. Biotech Software and Internet Report, 3, 146.

282. Singh, Harpreet, & Raghava, G. P. S. (2002). Detection of Orientation of MHC Class II Binding Peptides Using Bioinformatics Tools. Biotech Software & Internet Report: The Computer Software Journal for Scientists, 3(5–6), 146–150.

283. Raghava, G. P. S. (2001). A graphical web server for the analysis of protein sequences and alignment. Biotech Software & Internet Report: The Computer Software Journal for Scientists, 2(6), 254–257.

284. Raghava, G. P. S. (2001). A web server for computing the size of DNA/protein fragments using a graphical method. Biotech Software & Internet Report: The Computer Software Journal for Scient, 2(5), 198–200.

285. Raghava, G. P. S. (2001). PDSB: Public domain software in biology. Biotech Software & Internet Report: The Computer Software Journal for Scient, 2(4), 154–156.

286. Raghava, G. P. S. (2001). PDWSB: public domain web servers in biology. Biotech Software & Internet Report: The Computer Software Journal for Scient, 2(4), 152–153.

287. Raghava, G. P. S., & Agrewala, J. N. (2001). A Web-based Method for Computing Endpoint Titer and Concentration of Antibody/Antigen. Biotech Software & Internet Report: The Computer Software Journal for Scient, 2(5), 196–197.

288. Singh, H., & Raghava, G. P. S. (2001). ProPred: prediction of HLA-DR binding sites. Bioinformatics, 17(12), 1236–1237.

289. Raghava, G P S. (2000). Protein secondary structure prediction using nearest neighbor and neural network approach. CASP, 4, 75–76.

290. Raghava, Gajendra P S, Solanki, R. J., Soni, V., & Agrawal, P. (2000). Fingerprinting method for phylogenetic classification and identification of microorganisms based on variation in 16S rRNA gene sequences. Biotechniques, 29(1), 108–115.

291. Raghava, G. (1999). A computer program for predicting the protein structural classes. J. Biosciences, 24, 176.

292. Nihalani, D., Raghava, G. P. S., & Sahni, A. N. G. (1997). Mapping of the plasminogen binding site of. Protein Science, 6, 1234–1292.

293. Nihalani, D., Raghava, G. P. S., & Sahni, G. (1997). Mapping of the plasminogen binding site of streptokinase with short synthetic peptides. Protein Science, 6(6), 1284–1292.

294. Raghava, G. P. (1995). DNAOPT: a computer program to aid optimization of DNA gel electrophoresis and SDS-PAGE. Biotechniques, 18(2), 274–278.

295. Agrewala, J. N., Raghava, G. P. S., & Mishra, G. C. (1994). Measurement and computation of murine interleukin-4 and interferon-7 by exploiting the unique abilities of these lymphokines to induce the secretion of iggl and IgG2a. Journal of Immunoassay.

296. Raghava, G. P. S. (1994). Improved estimation of DNA fragment length from gel electrophoresis data using a graphical method. Biotechniques, 17(1), 100–104.

297. Raghava, G. P. S. (1994). Recent excitement about artificial neural networks. Biobytes, 3, 4–5.

298. Raghava, G. P. S., Goel, A., Singh, A. M., & Varshney, G. C. (1994). A simple microassay for computing the hemolytic potency of drugs. Biotechniques, 17(6), 1148–1153.

299. Raghava, G. P. S., & Sahni, G. (1994). GMAP: a multi-purpose computer program to aid synthetic gene design, cassette mutagenesis and the introduction of potential restriction sites into DNA sequences. Biotechniques, 16(6), 1116–1123.

300. Ragliava, G. P. S., & Agrewala, J. N. (1994). Method for determining the affinity of monoclonal antibody using non-competitive ELISA: a computer program. Journal of Immunoassay, 15(2), 115–128.

301. Raghava, G. P. S., Joshi, A. K., & Agrewala, J. N. (1992). Calculation of antibody and antigen concentrations from ELISA data using a graphical method. Journal of Immunological Methods, 153(1–2), 263–264.

302. Tripathy, S. C., Balasubramantan, R., Raghava, G. P. S., & Chatterjee, J. K. (1988). Microprocessor based active and reactive power measurement. Journal of the Institution of Engineers. India. Electrical Engineering Division, 69(2), 73–77.