Author

Adam Novak

University of California, Santa Cruz

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· 2 Genomics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:benchmarking· 2 Approach:statistical model· 2 Research Focus:batch correction / integration· 1 Assay:bulk RNA-seq· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Organism:human· 1

Frequent Co-Authors

Benedict PateniD· 3 shared Alden D. Deran· 1 shared Ali GhaffaariiD· 1 shared Anthony D. JosephiD· 1 shared Arjun Rao· 1 shared Audrey Musselman-Brown· 1 shared Bas E Dutilh· 1 shared Ben Langmead· 1 shared

Activity by Year

2016-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 27 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 papersBioinformatics

Benedict PatenORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Hub labeling makes exact distance calculation practical for large human pangenome graphs

Zia Truong, Adam Novak, Benedict Paten

The paper introduces a hub labeling method to reduce the space required for distance indexing in large pangenome graphs, improving query support and reducing storage needs.

bioRxiv · Nov 6, 2026 · PreprintBioinformatics

Computational Pan-Genomics: Status, Promises and Challenges

Tobias Marschall, Manja Marz, Thomas Abeel, Louis Dijkstra, Bas E Dutilh, Ali Ghaffaari, Paul Kersey, Wigard Kloosterman, Veli Makinen, Adam Novak, Benedict Paten, David Porubsky, Eric RIVALS, Can Alkan, Jasmijn Baaijens, , Pisan

This paper reviews computational pan-genomics, discussing its status, potential, and challenges across multiple biological disciplines.

Briefings in Bioinformatics · Oct 21, 2016Peer-reviewedGenomics

Rapid and efficient analysis of 20,000 RNA-seq samples with Toil

John Vivian, Arjun Rao, Frank Austin Nothaft, Christopher Ketchum, Joel Armstrong, Adam Novak, Jacob Pfeil, Jake Narkizian, Alden D. Deran, Audrey Musselman-Brown, Hannes Schmidt, Peter Amstutz, Brian Craft, Mary Goldman, Kate Rosenbloom, , Benedict Paten

The paper demonstrates Toil's ability to efficiently process 20,000 RNA-seq samples to create a batch-effect-free meta-analysis across five datasets.

bioRxiv · Jul 7, 2016Bioinformatics