Author

Ayesha Bajwa

University of California, Berkeley

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

Genomics· 2

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:benchmarking· 2 Assay:DNA methylation· 2 Organism:human· 2 Research Focus:variant effect prediction· 2 Approach:deep learning· 1 Research Focus:gene regulatory network inference· 1 Assay:long-read sequencing· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Nilah M. IoannidisiD· 2 shared Aaron StreetsiD· 1 shared Andrew StergachisiD· 1 shared Mitchell Robert VollgeriD· 1 shared Oberon Dixon-LuinenburgiD· 1 shared Pooja KathailiD· 1 shared Richard W. ShuaiiD· 1 shared Ruchir RastogiiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 16 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

2 shared papersGenomics

Nilah M. IoannidisORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Epigenetic conditioning improves sequence-based modeling of gene regulation across cell types and alleles

Oberon Dixon-Luinenburg, Ayesha Bajwa, Mitchell Robert Vollger, Andrew Stergachis, Aaron Streets, Nilah M. Ioannidis

This paper introduces MethylSeqNet, a model that improves sequence-based gene regulation predictions by conditioning on CpG methylation, showing benefits for cell-type-specific regulation and allele-specific phenomena.

bioRxiv · Jun 7, 2026 · PreprintGenomics

Characterizing uncertainty in predictions of genomic sequence-to-activity models

Ayesha Bajwa, Ruchir Rastogi, Pooja Kathail, Richard W. Shuai, Nilah M. Ioannidis

This study examines uncertainty in genomic sequence-to-activity model predictions by analyzing consistency across different sequence types and identifies areas where models perform poorly.

bioRxiv · Dec 21, 2023 · PreprintGenomics