Author

Say Li Kong

Agency for Science, Technology and Research

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 2 Approach:statistical model· 2 Assay:ATAC-seq· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Assay:ChIP-seq· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Vibhor KumariD· 2 shared Debarka SenguptaiD· 1 shared Indra Prakash JhaiD· 1 shared Madhu SharmaiD· 1 shared Neetesh Pandey· 1 shared Omkar ChandraiD· 1 shared Shreya V. MishraiD· 1 shared Smriti Chawla· 1 shared

Activity by Year

2020-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersBioinformatics

Vibhor KumarORCID

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2 papers

Recent·Most cited

Inferring functions of coding and non-coding genes using epigenomic patterns and deciphering the effect of combinatorics of transcription factors binding at promoters

Omkar Chandra, Madhu Sharma, Neetesh Pandey, Indra Prakash Jha, Shreya V. Mishra, Say Li Kong, Vibhor Kumar

The paper predicts gene functions using epigenomic patterns and TF binding, achieving high accuracy and validating results with CRISPR screens and PubMed data.

bioRxiv · Apr 17, 2022 · PreprintBioinformatics

UniPath: A uniform approach for pathway and gene-set based analysis of heterogeneity in single-cell epigenome and transcriptome profiles.

Smriti Chawla, Sudhagar Samydurai, Say Li Kong, Zhengwei Wu, Zhenxun Wang, Wai Leong Tam, Debarka Sengupta, Vibhor Kumar

UniPath uses pathway and gene-set enrichment scores to analyze single-cell epigenome and transcriptome data, revealing biologically meaningful co-clustering and aiding in cancer cell regulation inference.

Nucleic Acids Research · Nov 13, 2020Peer-reviewedGenomics