Editorial or Reviewer Role in Peer-Reviewed Journals
Frontiers in Public Health: Associate Editor
Frontiers in Oncology: Associate Editor & Reviewer
BMC Bioinformatics: Editorial Board Member
Springer Nature - Discover Oncology: Editorial Board Member
MDPI - International Journal of Molecular Sciences: Guest Editor
Frontiers in Genetics: Reviewer
Frontiers in Molecular Biosciences: Reviewer
Computers in Biology & Medicine: Reviewer
Springer Nature - Scientific Reports: Reviewer
Science Society Membership
Associate Member - AACR - American Association for Cancer Research
EASL – European Association for study of liver disease
ISCB - International Society of Computational Biology
Member of Asia Pacific Bioinformatics Network (APBIONET)
Member of BIOinformatics CLUb for Experimenting Scientists (Bioclues)
Participation in International Scientific Competitions
NCI-CPTAC DREAM Proteogenomics Challenge, 2017 (Sub Challenge 1, Sub Challenge 2, Sub Challenge 3 )
Multiple Myeloma DREAM Challenge, 2017 (Sub Challenge 1, Sub Challenge 2)
DREAM Preterm Birth Prediction Challenge, Transcriptomics, 2019 (Sub Challenge 1, Sub Challenge 2)
Single Cell Signaling in Breast Cancer Challenge, 2019 (Sub Challenge 1, Sub Challenge 2, Sub Challenge 3, Sub Challenge 4)
Reviewer and Judges role in International Conferences
Judge for Poster Presentation in Research Symposium 2021
Judge for Poster Presentation in OmicsLogic Research Symposium 2022
Judge for Poster Presentation in NIH Summer Postbacs 2023
Judge for Poster Presentation in NIH Summer Postbacs 2024
Edited or Reviewed Publications
Edited Publications
Noh S, Firdaus M and Rhee K-H (2023) Commentary: Integrated blockchain-deep learning approach for analyzing the electronic health records recommender system. Front. Public Health 11:1133142. doi: 10.3389/fpubh.2023.1133142
Ayadi H, Bour C, Fischer A, Ghoniem M and Fagherazzi G (2023) The Long COVID experience from a patient's perspective: a clustering analysis of 27,216 Reddit posts. Front. Public Health 11:1227807. doi: 10.3389/fpubh.2023.1227807
Reviewed Publications
Ju A, Tang J, Chen S, Fu Y and Luo Y (2021) Pyroptosis-Related Gene Signatures Can Robustly Diagnose Skin Cutaneous Melanoma and Predict the Prognosis. Front. Oncol. 11:709077. doi: 10.3389/fonc.2021.709077
Li J, Tian X, Nie Y, He Y, Wu W, Lei X, Zhang T, Wang Y, Mao Z, Zhang H, Zhang X and Song W (2022) BTBD10 is a Prognostic Biomarker Correlated With Immune Infiltration in Hepatocellular Carcinoma. Front. Mol. Biosci. 8:762541. doi: 10.3389/fmolb.2021.762541
Huang S, Lyu S, Gao Z, Zha W, Wang P, Shan Y, He J and Li Y (2021) m6A-Related lncRNAs Are Potential Biomarkers for the Prognosis of Metastatic Skin Cutaneous Melanoma. Front. Mol. Biosci. 8:687760. doi: 10.3389/fmolb.2021.687760
Zhang W, Xie X, Huang Z, Zhong X, Liu Y, Cheong K-L, Zhou J and Tang S (2022) The integration of single-cell sequencing, TCGA, and GEO data analysis revealed that PRRT3-AS1 is a biomarker and therapeutic target of SKCM. Front. Immunol. 13:919145. doi: 10.3389/fimmu.2022.919145
Koufaris C and Kirmizis A (2021) Identification of NAA40 as a Potential Prognostic Marker for Aggressive Liver Cancer Subtypes. Front. Oncol. 11:691950. doi: 10.3389/fonc.2021.691950
Feng X, Mu S, Ma Y and Wang W (2021) Development and Verification of an Immune-Related Gene Pairs Prognostic Signature in Hepatocellular Carcinoma. Front. Mol. Biosci. 8:715728. doi: 10.3389/fmolb.2021.715728
Zhou X, Rong R, Xiong S, Song W, Ji D and Xia X (2022) Integrated analysis to reveal potential therapeutic targets and prognostic biomarkers of skin cutaneous melanoma. Front. Immunol. 13:914108. doi: 10.3389/fimmu.2022.914108
Dong Y, Zhao Z, Simayi M, Chen C, Xu Z, Lv D and Tang B (2022) Transcriptome profiles of fatty acid metabolism-related genes and immune infiltrates identify hot tumors for immunotherapy in cutaneous melanoma. Front. Genet. 13:860067. doi: 10.3389/fgene.2022.860067
Akbar S, Ahmad A, Hayat M, Rehman AU, Khan S, Ali F. iAtbP-Hyb-EnC: Prediction of antitubercular peptides via heterogeneous feature representation and genetic algorithm based ensemble learning model. Comput Biol Med. 2021 Oct;137:104778. doi: 10.1016/j.compbiomed.2021.104778. Epub 2021