Author

P. Polak

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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Immunology· 4 Cancer Biology· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 5 Organism:human· 5 Assay:CITE-seq· 2 Research Focus:gene regulatory network inference· 2 Approach:machine learning (classical)· 2 Assay:scRNA-seq· 2 Approach:statistical model· 2 Research Focus:clustering· 1

Frequent Co-Authors

G. Yaari· 4 shared A. M. Collins· 2 shared A. Peres· 2 shared A. Breister· 1 shared A. Danyi· 1 shared A. Levy-Barda· 1 shared A. Omer· 1 shared A. Peretz· 1 shared

Activity by Year

2019-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 16 mutual co-author links

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4 shared papersImmunology

G. Yaari

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Author profile →

6 papers

Recent·Most cited

IGHV allele similarity clustering improves genotype inference from adaptive immune receptor repertoire sequencing data

A. Peres, W. D. Lees, O. L. Rodriguez, N. Y. Lee, P. Polak, R. Hope, M. Kedmi, A. M. Collins, M. Ohlin, S. H. Kleinstein, C. Watson, G. Yaari

The paper introduces a new V allele naming scheme and genotype inference method for adaptive immune receptor sequencing, validated with genomic long read data and implemented in an R package.

bioRxiv · Dec 26, 2022 · PreprintImmunology

Altered somatic hypermutation patterns in COVID-19 patients classifies disease severity

M. Safra, Z. Tamari, P. Polak, S. Shiber, M. Matan, H. Karameh, Y. Helviz, A. Levy-Barda, V. Yahalom, A. Peretz, E. Ben-Chetrit, B. Brenner, T. Tuller, M. Gal-Tanamy, G. Yaari

This study uses machine learning to analyze B cell receptor sequencing data and identifies altered somatic hypermutation patterns in COVID-19 patients that correlate with disease severity.

bioRxiv · Dec 20, 2022 · PreprintImmunology

Diversity and distribution of sulfur metabolism in the human gut microbiome and its association with colorectal cancer

P. G. Wolf, E. S. Cowley, A. Breister, S. Matatov, L. Lucio, P. Polak, J. M. Ridlon, H. R. Gaskins, K. Anantharaman

The paper examines sulfur metabolism in the human gut microbiome, finding it more diverse and associated with colorectal cancer.

bioRxiv · Jul 1, 2021 · PreprintMicrobiology

T Cell Receptor Beta Germline Variability is Revealed by Inference From Repertoire Data

A. Omer, A. Peres, O. L. Rodrigues, C. T. Watson, W. Lees, P. Polak, A. M. Collins, G. Yaari

The paper identifies undocumented polymorphisms in T cell receptor Beta genes using AIRR-seq data and shows how a single SNP affects TCR repertoire composition.

bioRxiv · May 17, 2021Immunology

Machine learning analysis of naïve B-cell receptor repertoires stratifies celiac disease patients and controls

O. Shemesh, P. Polak, K. E. A. Lundin, L. M. Sollid, G. Yaari

The paper uses machine learning to analyze naive B-cell receptor repertoires to distinguish celiac disease patients from controls, achieving an F1 score of 85%.

bioRxiv · Nov 9, 2020Immunology

A deep learning system can accurately classify primary and metastatic cancers based on patterns of passenger mutations

W. Jiao, G. Atwal, P. Polak, R. Karlic, E. Cuppen, A. Danyi, J. de Ridder, C. van Herpen, M. P. Lolkema, N. Steeghs, G. Getz, Q. D. Morris, L. D. Stein, PCAWG Pathology & Clinical Correlates Working Grp, ICGC/TCGA Pan-cancer Analysis of Whole Genomes Net

This paper develops a deep learning classifier using whole genome sequencing data to distinguish cancer types and identify metastatic origins.

bioRxiv · Jan 22, 2019 · PreprintCancer Biology