Author

Rajesh Ilango

Arc Research Institute

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

Biology Disciplines

Click to filter author papers

Bioinformatics· 3 Genomics· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Assay:scRNA-seq· 3 Research Focus:software / tool· 3 Approach:statistical model· 3 Research Focus:benchmarking· 2 Approach:deep learning· 2 Organism:human· 2 Approach:machine learning (classical)· 2 Approach:transformer / foundation model· 2

Frequent Co-Authors

Chiara Ricci-TamiD· 3 shared Dave P. Burke· 3 shared Hani GoodarziiD· 3 shared Patrick D. HsuiD· 3 shared Abhinav AdduriiD· 2 shared Alexander DobiniD· 2 shared Jeremy Sullivan· 2 shared Mohsen NaghipourfariD· 2 shared

Activity by Year

2022-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersSystems Biology

Chiara Ricci-TamORCID

Mutual co-authors in cluster

Author profile →

5 papers

Recent·Most cited

Predicting cellular responses to perturbation across diverse contexts with STATE

Abhinav Adduri, Dhruv Gautam, Beatrice Bevilacqua, Mohsen Naghipourfar, Alishba Imran, Rohan Shah, Noam Teyssier, Rishi Verma, Christopher Carpenter, Basak Eraslan, Francis Chalissery, Rajesh Ilango, Vishvak Subramanyam, Chiara Ricci-Tam, Sanjay Nagaraj, , Yusuf Roohani

State, a set-based transformer trained on over 100 million perturbed cells, predicts perturbation responses in new cellular contexts better than mean, linear and deep learning baselines.

Cell · Aug 31, 2026Peer-reviewedSystems Biology✦ In-depth digest

scBaseCount: an AI agent-curated, uniformly processed, and autonomously updated single cell data repository

Nicholas D. Youngblut, Christopher F Carpenter, Arshia Nayebnazar, Abhinav Adduri, Rohan Shah, Chiara Ricci-Tam, Jaanak Prashar, Rajesh Ilango, Noam Teyssier, Silvana Konermann, Patrick D. Hsu, Alexander Dobin, Dave P. Burke, Hani Goodarzi, Yusuf Roohani

scBaseCount is a single-cell RNA sequencing database that automates metadata extraction and data processing using AI, offering a large, standardized collection of gene expression data across multiple organisms and tissues.

bioRxiv · Feb 27, 2025 · PreprintBioinformatics

Genome modeling and design across all domains of life with Evo 2

Garyk Brixi, Matthew G. Durrant, Jerome Ku, Michael Poli, Greg Brockman, Daniel Chang, Gabriel A. Gonzalez, S. B. King, David B. Li, Aditi T. Merchant, Mohsen Naghipourfar, Eric Nguyen, Chiara Ricci-Tam, David W. Romero, Gwanggyu Sun, , Brian Hie

A 40B-parameter DNA model trained on 9.3 trillion tokens scores coding and noncoding variants zero-shot, exposes interpretable sequence features, and writes chromosome-scale sequences.

bioRxiv · Feb 18, 2025 · PreprintGenomics✦ In-depth digest

AlphaPept, a modern and open framework for MS-based proteomics

Maximilian T. Strauss, Isabell Bludau, Wen‐Feng Zeng, Eugenia Voytik, Constantin Ammar, Julia Patricia Schessner, Rajesh Ilango, Michelle L. Gill, Florian Meier, Sander Willems, Matthias Mann

AlphaPept is an open-source framework for efficient processing of large MS-based proteomics datasets, achieving significant speed improvements using Python and machine learning.

Nature Communications · Mar 9, 2024Peer-reviewedBioinformatics

Accelerating single-cell genomic analysis with GPUs

Corey Nolet, Avantika Lal, Rajesh Ilango, Taurean Dyer, Rajiv Movva, John Zedlewski, Johnny Israeli

The paper demonstrates the use of GPU computing with RAPIDS to accelerate single-cell genomic analysis workflows and provides open-source examples.

bioRxiv · May 26, 2022 · PreprintBioinformatics