Lab Publications

Legend:
* Equal Contribution
† Co-corresponding Authors
Underlined names are undergraduate student members of our lab.

Pre-prints

Atishay Jain*, Tuan M. Pham*, David H. Laidlaw, Ying Ma, and R. Singh. “Diffusion-based Representation Integration for Foundation Models Improves Spatial Transcriptomics Analysis.” [Code]

Jien Li*, Zhenke Liu*, Ziqi Zhang*, Jiaqi Zhang, and R. Singh. “From Circles to Signals: Representation Learning on Ultra-Long Extrachromosomal Circular DNA.” [Code]

Samantha Bock, Luke A Hoekstra, Kelsi Hagerty, Robert E Schmidt, Jessica Judson, Maxwell Adorsoo, R. Singh, Fredric J Janzen, Anne M Bronikowski. “Widespread sex-biased gene expression reflects female-biased longevity in a species with environmental sex determination .“

Wenjun Zhao, Alma Plaza-Rodriguez, Pichayathida Luanpaisanon, Elena Xinyi Wang, Linnéa Gyllingberg, R. Singh, Elana Fertig†, and Genevieve L. Stein-O’Brien†. “Inferring the regulation dynamics of oscillatory networks from scRNA-seq data.” [Code]

Doudou Yu, Jurgen Germann, Ghulam Murtaza, Kaitlyn Hajdarovic, Kelsey Babcock, Shiva Dehkordi, Alexander Jackson, Ivana Delalle, Miranda Orr, Habil Zare, R. Singh, William S. Noble, Andrei Vlassenko, Manu Goyal, Ashley Webb. “HypoAD: volumetric and single-cell analysis reveals changes in the human hypothalamus in aging and Alzheimer’s disease.”

Michal Golovanevsky*, Pranav Mahableshwarkar*, Carsten Eickhoff†, and R. Singh†. “PiCME: Pipeline for Contrastive Modality Evaluation and Encoding in the MIMIC Dataset.” [Code]

Nikolai Tennant*, Ananya Pavuluri*, Gunjan Singh, Kate M. O’Connor-Giles, Erica Larschan†, and R. Singh†. “TimeFlies: an snRNA-seq aging clock for the fruit fly head sheds light on sex-biased aging.” [Code]

Jiaqi Zhang, Manav Chakravarthy, and R. Singh. “scMultiNODE: Integrative Model for Multi-Modal Temporal Single-Cell Data.” [Code]

Pinar Demetci, Quang Huy Tran, Ievgen Redko^†, and R. Singh^†. “Jointly aligning cells and genomic features of single-cell multi-omics data with co-optimal transport” [Code], selected talks at the Machine Learning in Computational Biology conference (MLCB 2022) and Learning Meaningful Representations of Life (LMRL) workshop at NeurIPS 2022..

In press

Colin D. Baker, Tuan M. Pham, Pinar Demetci, Quang-Huy Tran, Ievgen Redko, Bjorn Sandstede, and R. Singh. “SCOT+: A Comprehensive Software Suite for Single-Cell alignment Using Optimal Transport.” [Code], to appear in Bioinformatics Advances.

2025

Michal Golovanevsky*, William Rudman*, Michael Lepori, Amir Bar, R. Singh†, and Carsten Eickhoff†. “Pixels Versus Priors: Controlling Knowledge Priors in Vision-Language Models through Visual Counterfacts.” [Code], Empirical Methods in Natural Language Processing (EMNLP) 2025.

Atishay Jain, David H. Laidlaw, Ying Ma, and R. Singh. “Improved Spatial Transcriptomics Clustering with Nested Graph Neural Networks.” [Code], ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB) 2025.

Jessica A. Patricoski-Chavez, Seema Nagpal, R. Singh, Jeremy L. Warner, and Ece D. Gamsiz Uzun. “A deep learning model to predict glioma recurrence using integrated genomic and clinical data.” [Code], Communications Medicine.

Yusuke Suita*, Hardy Bright*, Yuan Pu, Merih Deniz Toruner, Jordan Idehen, Nikos Tapinos†, and R. Singh†. “Machine learning on multiple epigenetic features reveals H3K27Ac as a driver of gene expression prediction across patients with glioblastoma.” [Code], PLOS Computational Biology.

William Rudman*, Michal Golovanesky*, Amir Bar, Vedant Palit, Yann LeCun, Carsten Eickhoff†, and R. Singh†. “Forgotten Polygons: Multimodal Large Language Models are Shape-Blind.” [Code], Association for Computational Linguistics (ACL) Findings 2025.

Tassallah Abdullahi, Ioanna Gemou, Nihal V. Nayak, Ghulam Murtaza, Stephen H. Bach, Carsten Eickhoff†, and R. Singh†. “K-Paths: Reasoning over Graph Paths for Drug Repurposing and Drug Interaction Prediction.” [Code], ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) 2025.

Whitney Sloneker, Shalin Patel, Michael Wang, Lorin Crawford†, and R.Singh†. “BetaExplainer: A Probabilistic Method to Explain Graph Neural Networks.” [Code] Special Issue of Journal of Statistical Theory and Applications.

Wenjun Zhao, Erica Larschan, Björn Sandstede†, and R. Singh†. “Optimal transport reveals dynamic gene regulatory networks via gene velocity estimation.” [Code], PLOS Computational Biology.

Michal Golovanevsky*, William Rudman*, Vedant Palit, R. Singh†, and Carsten Eickhoff†. “What Do VLMs NOTICE? A Mechanistic Interpretability Pipeline for Noise-free Text-Image Corruption and Evaluation.” North American Chapter of the Association for Computational Linguistics (NAACL) Conference 2025

Sara Zeppilli, Alonso Ortega Gurrola, Pinar Demetci, David H. Brann, Tuan M. Pham, Robin Attey, Noga Zilkha, Tali Kimchi, Sandeep R. Datta, R. Singh, Maria A. Tosches, Anton Crombach^†, and Alex Fleischmann^†, “Mammalian olfactory cortex neurons retain molecular signatures of ancestral cell types.“, Nature Neuroscience.

Michal Golovanevsky, Eva Schiller, Akira Nair, Eric Han, R. Singh†, and Carsten Eickhoff†, “One-Versus-Others Attention: Scalable Multimodal Integration for Clinical Data.” [Code],Pacific Symposium on Biocomputing (PSB) 2025.

Lucas Paulo de Lima Camillo^†, Muhammad Haider Asif, Steve Horvath, Erica Larschan, and R. Singh^†, “Histone mark age of human tissues and cells.” [Code], Science Advances.

2024

Ghulam Murtaza, Justin M. Wagner, Justin M. Zook, and R. Singh. “GrapHiC: An integrative graph-based approach for imputing missing Hi-C reads.” [Code], IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB).

Conor R. Walker, Xiaoting Li, Manav Chakravarthy, William Lounsbery-Scaife, Yoolim A. Choi, R. Singh, Gamze Gürsoy. “Private information leakage from single-cell count matrices.” Cell.

Jiaqi Zhang, Erica Larschan, Jeremy Bigness†, and R. Singh†. “scNODE: Generative Model for Temporal Single Cell Transcriptomic Data Prediction.” [Code], European Conference on Computational Biology (ECCB) 2024 (Proceedings in Bioinformatics).

Tassallah Amina Abdullahi, R. Singh†, and Carsten Eickhoff†. “Retrieval Augmented Zero-Shot Text Classification.“, [Code], ACM International Conference on the Theory of Information Retrieval (ICTIR) 2024.

Ghulam Murtaza, Byron Butaney, Justin Wagner, and R. Singh. “scGrapHiC: Deep learning-based graph deconvolution for Hi-C using single cell gene expression.” [Code], Intelligent Systems in Molecular Biology (ISMB) 2024 (Proceedings in Bioinformatics) [runner up for Ian Lawson Van Toch Best Paper Award]

Tassallah Amina Abdullahi, Laura Mercurio, R. Singh†, and Carsten Eickhoff†, “Retrieval-Based Diagnostic Decision Support” [Code], JMIR Medical Informatics.

Pinar Demetci, Quang Huy Tran, Ievgen Redko^†, and R. Singh^†, “Revisiting invariances and introducing priors in Gromov-Wasserstein distances” [Code], Artificial Intelligence and Statistics (AISTATS) 2024.

Suchen Zheng*, Nitya Thakkar*, Hannah L. Harris, Megan Zhang, Susanna Liu, Mark Gerstein, Erez Lieberman Aiden, Jordan Rowley, William S. Noble, Gamze Gürsoy^†, and R. Singh^†. “Predicting A/B compartments from histone modifications using deep learning.” [Code], iScience (ACM BCB 2023 Special Issue).

Tassallah Amina Abdullahi, R. Singh^†, and Carsten Eickhoff^†, “Learning to Make Rare and Complex Diagnoses with Generative AI Assistance.”, JMIR Medical Education.

2023

Ghulam Murtaza, Atishay Jain, Madeline Hughes, Justin M. Wagner, and R. Singh. “Investigating the performance of deep learning methods for Hi-C resolution improvement.” [Code], Genes.

Doudou Yu, Manlin Li, Guangjie Linghu, Yihuan Hu, Kaitlyn H. Hajdarovic, An Wang, R. Singh^†, and Ashley E. Webb^†. “CellBiAge: Improved single-cell age classification using data binarization“. [Code], Cell Reports.

Atishay Jain, David Laidlaw, Peter Bajcsy^†, and R. Singh^†. “Memory Efficient Segmentation of Large Microscopy Images Using Graph-based Neural Networks.” [Code], Microscopy.

Jiaqi Zhang and R. Singh. “Investigating the Complexity of Gene Co-expression Estimation for Single-cell Data.” [Code], Journal of Machine Learning for Modeling and Computing (JMLMC).

Charlotte Guetta-Terrier, David Karambizi, Bedia Akosman, Jia-Shu Chen, Suchitra Kamle, J Eduardo Fajardo, Andras Fiser, R. Singh, Steven A Toms, Chun Geun Lee, Jack A Elias, Nikos Tapinos. “Chi3l1 is a modulator of glioma stem cell states and a therapeutic vulnerability for glioblastoma.”, Cancer Research.

Quang Huy Tran, Hicham Janati, Nicolas Courty^†, Rémi Flamary^†, Ievgen Redko, Pinar Demetci, and R. Singh (ordering based on contribution). “Unbalanced CO-Optimal Transport“, AAAI Conference on Artificial Intelligence.

Adam Berkley, Camillo Saueressig, Utkarsh Shukla, Imran Chowdhury, Anthony Munoz-Gauna, Olalekan Shehu, and R. Singh^†, and Reshma Munbodh^†. “Clinical Capability of Modern Brain Tumor Segmentation Models“, Medical Physics.

2022

Michal Golovanevsky, Carsten Eickhoff^†, and R. Singh^†. “Multimodal Attention-based Deep Learning for Alzheimer’s Disease Diagnosis“, Journal of the American Medical Informatics Association (JAMIA). [Code]

Camillo Saueressig, Adam Berkley, Reshma Munbodh^†, and R. Singh^†. “A Joint Graph and Image Convolution Network for Automatic Brain Tumor Segmentation“, Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, Lecture Notes in Computer Science (LNCS, Springer). [Code]

Pinar Demetci, Rebecca Santorella, Björn Sandstede, and R. Singh. “Unsupervised integration of single-cell multi-omics datasets with disparities in cell-type representation“, International Conference on Research in Computational Molecular Biology (RECOMB). [Website][Code]
Extended version: Pinar Demetci, Rebecca Santorella, Manav Chakravarthy, Björn Sandstede, and R. Singh. “SCOTv2: Single-Cell Multiomic Alignment with Disproportionate Cell-Type Representation“, Journal of Computational Biology (Special RECOMB Issue).

Lucas Paulo de Lima Camillo^†, Louis R Lapierre, and R. Singh^†. “AltumAge: A Pan-Tissue DNA-Methylation Epigenetic Clock Based on Deep Learning“, npj Aging. [Code]

Jeremy Bigness, Xavi Loinaz, Shalin Patel, Erica Larschan, and R. Singh. “Integrating long-range regulatory interactions to predict gene expression using graph convolutional networks“, Journal of Computational Biology. [Talk][Code]

Chris K. Kim, Ji Whae Choi, and others. “An automated pipeline for rapid triage of COVID-19 patients using artificial
intelligence based on chest radiographs and clinical data“, npj Digital Medicine.

2021

Giancarlo Bonora, Vijay Ramani, R. Singh, He Fang, Dana Jackson, Sanjay Srivatsan, Ruolan Qiu, Choli Lee, Cole Trapnell, Jay Shendure, Zhijun Duan, Xinxian Deng, William S. Noble, and Christine M. Disteche. “Single-cell landscape of nuclear configuration and gene expression during stem cell differentiation and X inactivation“, Genome Biology.

Pinar Demetci*, Rebecca Santorella*, Björn Sandstede, William S. Noble, and R. Singh. “Gromov-Wasserstein optimal transport to align single-cell multi-omics data.”, International Conference on Research in Computational Molecular Biology (RECOMB). [Website][Code]
Extended version: Pinar Demetci*, Rebecca Santorella*, Björn Sandstede, William S. Noble, and R. Singh. “SCOT: Single-cell multi-omics alignment with optimal transport“, Journal of Computational Biology (Special RECOMB Issue).

Ashley Mae Conard, Nathaniel Goodman, Yanhui Hu, Norbert Perrimon, R. Singh, Charles Lawrence, and Erica Larschan. “TIMEOR: a web-based tool to uncover temporal regulatory mechanisms from multi-omics data“, Nucleic Acids Research. [Website]

Jacob Schreiber and R.Singh. “Machine learning for profile prediction in genomics“, Current Opinion in Chemical Biology. [Invited paper]

Camillo Saueressig, Adam Berkley, Ellliot Kang, Reshma Munbodh^†, and R. Singh^†. “Exploring graph-based neural networks for automatic brain tumor segmentation.”, From Data to Models and Back, Lecture Notes in Computer Science (LNCS, Springer).

2020

R. Singh, Pinar Demetci, Giancarlo Bonora, Vijay Ramani, Choli Lee, He Fang, Zhijun Duan, Xinxian Deng, Jay Shendure, Christine Disteche, and William S. Noble. “Unsupervised manifold alignment for single-cell multi-omics data“, ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB)
[Talk][Code]

Jacob Schreiber, R.Singh, Jeffrey Bilmes and William S. Noble. “A pitfall for machine learning methods aiming to predict across cell types“, Genome Biology

Derek Blakely, Eamon Collins, R. Singh, Andrew Norton, Jack Lanchantin, and Yanjun Qi. “FastSK: Fast Sequence Analysis with Gapped String Kernels“, Bioinformatics (Proceedings of the European Conference on Computational Biology (ECCB)) [Code]