Research and Publications

List of Publications:

Journals


  1. N. Subramanian and R. Bose, "Dipole angular entropy techniques for intron-exon segregation in DNA", Euro Physics Letters, vol. 98, no. 2, p. 28002, 2012.

    • This paper deals with the classical problem of intron-exon segmentation using a form of "structural entropy" of the DNA. To compute the structural entropy, we employ a physio-chemical property of the DNA (viz.) the dipole moment of the bases, which is known to influence the unique double-helical structure of the DNA.

  2. N. Ramakrishnan and R. Bose, "Dipole entropy based techniques for segmentation of introns and exons in DNA", Appl. Phys. Lett., vol. 101, no. 8, p. 083701, 2012.

    • This paper delves deeper into the intron-exon segmentation using more advanced tools from Information theory (viz.) superinformation. Superinformation can be considered as "entropy of entropies" and is helpful in overcoming the averaging problem associated with entropy.

  3. Nithya Ramakrishnan and R.Bose, “Analysis of distribution of DNA methylation in kidney-renal-clear-cell-carcinoma specific genes using entropy”, Genomic Data, vol. 10, pp. 110-116, (2016).

      • This letter is about using Information theoretic tools such as entropy and mathematical transforms to predict cancer based on DNA methylation distribution across specific genes significant in cancer. We deal with a specific type of renal cancer (KIRC) due to the availability of sufficient data. Amongst other novelties, the concept of methylation entropy based on the levels of DNA methylation in a given CpG site is introduced.

  4. N. Ramakrishnan and R. Bose, “Analysis of healthy and tumour DNA methylation distributions in kidney-renal-clear-cell-carcinoma using Kullback–Leibler and Jensen–Shannon distance measures”, IET Systems Biology, vol. 11, no. 3, pp. 99-104, (2017)

      • This paper focuses on using advanced Information theoretic tools such as Kullback-Leibler distance and Jensen-Shannon distance for predicting a tumor methylation distribution. The paper also introduces the concept of an "average healthy methylation distribution".

5. N. Ramakrishnan, Sibiraj B. Pillai and R. Padinhateeri, "High fidelity epigenetic inheritance: Information theoretic model predicts k-threshold filling of histone modifications post replication" PLoS Comput Biol 18(2): e1009861.(2021)

Conferences (Posters)


1. Nithya Ramakrishnan,Mayuri Rege,Dibyendu Das, Sibiraj B.Pillai and Ranjith P., Computational Analysis of Histone Post-translational Modification Pairs and their Influence on Genes, EMBO Conference on Histone Chaperones, Crete, Greece, Oct 2019.

2. Nithya Ramakrishnan and R.Bose, “Analysis of DNA Methylation in Tumor Suppressor Genes using Information Theory”, Presented at the Cancer Genomics Conference at European Molecular Biological Institute (Heidelberg) pp. 161, 2015.

3. Nithya Ramakrishnan and R.Bose, “An Algorithm for the Generation of Random Numbers from DNA Methylation Data”, Presented at the Quantitative Principles in Biology Conference at European Molecular Biological Institute (Heidelberg) pp. 181, 2017.