Author

Neetesh Pandey

Indraprastha Institute of Information Technology Delhi

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· 6

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Approach:statistical model· 5 Organism:human· 3 Research Focus:benchmarking· 2 Research Focus:gene regulatory network inference· 2 Assay:scATAC-seq· 2 Assay:ATAC-seq· 1 Approach:benchmark study· 1 Assay:bulk RNA-seq· 1

Frequent Co-Authors

Shreya V. MishraiD· 5 shared Vibhor KumariD· 5 shared Omkar ChandraiD· 3 shared Indra Prakash JhaiD· 2 shared Madhu SharmaiD· 2 shared Aanchal MongiaiD· 1 shared Angshul MajumdariD· 1 shared Arjun RayiD· 1 shared

Activity by Year

2020-2025 · peak 2/yr

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10 top collaborators · 20 mutual co-author links

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5 shared papersBioinformatics

Shreya V. MishraORCID

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6 papers

Recent·Most cited

SAGA (Simplified Association Genomewide Analyses): a user-friendly Pipeline to Democratize Genome-Wide Association Studies

Basilio Cieza, Neetesh Pandey, Vivek Ruhela, Sarwan Ali, Giuseppe Tosto

SAGA is a user-friendly, automated pipeline that simplifies GWAS by integrating PLINK, GMMAT, and SAIGE, enabling non-experts to perform reproducible analyses.

bioRxiv · Aug 25, 2025 · PreprintBioinformatics

Searching match for single-cell open-chromatin profiles in large pools of single-cell transcriptomes and epigenomes for reference supported analysis

Shreya V. Mishra, Neetesh Pandey, Smriti Chawla, Madhu Sharma, Omkar Chandra, Indra Prakash Jha, Debarka Sengupta, Kedar Nath Natarajan, Vibhor Kumar

scEpiSearch enables accurate matching of single-cell open-chromatin profiles to large reference datasets, improving co-embedding and classification of epigenomic states across species and platforms.

Genome Research · Feb 1, 2023Peer-reviewedBioinformatics

An explainable model using Graph-Wavelet for predicting biophysical properties of proteins and measuring mutational effects

Shreya V. Mishra, Neetesh Pandey, Atul Rawat, Divyanshu Srivastava, Arjun Ray, Vibhor Kumar

The paper introduces a graph-wavelet model to predict protein biophysical properties and assess mutational effects by analyzing amino-acid features in protein structures.

IEEE Access · Jan 1, 2023Peer-reviewedBioinformatics

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

Improving chromatin-interaction prediction using single-cell open-chromatin profile and making insight about the cis-regulatory landscape of the human brain

Neetesh Pandey, Omkar Chandra, Shreya V. Mishra, Vibhor Kumar

The paper develops a method to predict both local and long-range chromatin interactions using single-cell open-chromatin profiles, revealing insights into cis-regulatory elements in the human brain.

bioRxiv · Dec 29, 2020 · PreprintBioinformatics

FITs: Forest of imputation trees for recovering true signals in single-cell open chromatin profiles

Rachesh Sharma, Neetesh Pandey, Aanchal Mongia, Shreya V. Mishra, Angshul Majumdar, Vibhor Kumar

FITs recovers true signals from sparse and noisy single-cell open-chromatin profiles by using a forest of imputation trees to avoid bias and preserve cell-type-specific activity.

NAR Genomics and Bioinformatics · Nov 19, 2020Peer-reviewedBioinformatics