Author

James M. Hogan

Queensland University of Technology

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· 2

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 2 Assay:protein sequence· 2 Research Focus:benchmarking· 1 Organism:human· 1 Research Focus:protein structure prediction· 1 Research Focus:sequence-to-function modeling· 1 Approach:statistical model· 1 Organism:yeast· 1

Frequent Co-Authors

Dhananjay KimothiiD· 2 shared Pravesh BiyaniiD· 2 shared Akshay SoniiD· 1 shared Melissa J. DavisiD· 1 shared Wayne KellyiD· 1 shared

Activity by Year

2020-2021 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 8 mutual co-author links

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2 shared papersBioinformatics

Dhananjay KimothiORCID

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2 papers

Recent·Most cited

BioinformaticsIEEE Transactions on Computational Biology and BioinformaticsPeer-reviewedDec 23, 2021

Sequence representations and their utility for predicting protein-protein interactions

Dhananjay Kimothi, Pravesh Biyani, James M. Hogan, Melissa J. Davis

This paper predicts protein-protein interactions using sequence encodings, achieving performance comparable to existing methods without complex physico-chemical features.

6 citations

humanyeast

BioinformaticsPLoS ONEPeer-reviewedMar 13, 2020

Learning supervised embeddings for large scale sequence comparisons

Dhananjay Kimothi, Pravesh Biyani, James M. Hogan…·Wayne Kelly

This paper introduces SuperVec and H-SuperVec, supervised methods for learning sequence embeddings that improve retrieval performance and speed compared to existing approaches.

7 citations

protein sequencestatistical model