Author

Ross L. Tellam

Commonwealth Scientific and Industrial Research OrganisationORCID 0000-0003-2353-1640Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 2 Approach:machine learning (classical)· 2 Assay:whole-genome sequencing· 2 Assay:ChIP-seq· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Organism:human· 1 Organism:mouse· 1

Frequent Co-Authors

Antônio ReverteriD· 1 shared Ben J. HayesiD· 1 shared Brian Paul DalrympleiD· 1 shared Hawlader Abdullah Al-MamuniD· 1 shared James KijasiD· 1 shared KLARA L. VERBYLAiD· 1 shared Laercio R. Porto NetoiD· 1 shared Marina Naval-SáncheziD· 1 shared

Activity by Year

2018-2022 · peak 1/yr

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10 top collaborators · 24 mutual co-author links

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1 shared paperGenomics

Antônio ReverterORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintApr 26, 2022

Detecting epistatic interactions in genomic data using Random Forests

Hawlader Abdullah Al-Mamun, Robert A. Dunne, Ross L. Tellam, KLARA L. VERBYLA

This paper introduces a computationally efficient Random Forests method to detect epistatic interactions in genomic data and validates it on simulated and real datasets.

5 citations

whole-genome sequencingmachine learning (classical)

𝕏 PostBluesky

GenomicsGigaSciencePeer-reviewedFeb 16, 2018

Mammalian genomic regulatory regions predicted by utilizing human genomics, transcriptomics and epigenetics data

Quan Hoang Nguyen, Ross L. Tellam, Marina Naval-Sánchez…·Brian Paul Dalrymple

The paper develops a computational method to predict regulatory regions in mammals using human genomics data, and applies it to cattle to prioritize variants and identify genome editing targets.

30 citations

humanmouse

𝕏 PostBluesky