Author

N. Riaz

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

Cancer Biology· 2 Biophysics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:statistical model· 3 Organism:human· 2 Research Focus:variant calling· 2 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Assay:imaging· 1 Assay:whole-exome sequencing· 1

Frequent Co-Authors

A. A. Jungbluth· 1 shared A. Apte· 1 shared A. Desrichard· 1 shared A. Gazzo· 1 shared A. Gupta· 1 shared A. Ho· 1 shared A. Iyer· 1 shared A. Marra· 1 shared

Activity by Year

2017-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 14 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

1 shared paperCancer Biology

A. A. Jungbluth

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

APOBEC3 mutagenesis drives therapy resistance in breast cancer

A. Gupta, A. Gazzo, P. Selenica, A. Safonov, F. Pareja, E. M. da Silva, D. N. Brown, Y. Zhu, J. Patel, J. Blanco-Heredia, B. Stefanovska, M. A. Carpenter, X. Pei, D. Frosina, A. A. Jungbluth, , S. Chandarlapaty

This study identifies APOBEC3 mutagenesis as a common driver of therapy resistance in breast cancer, associated with poorer clinical outcomes.

bioRxiv · Apr 29, 2024Cancer Biology

Reproducibility test of radiomics using network analysis and Wasserstein K-means algorithm

J. H. Oh, A. Apte, E. Katsoulakis, N. Riaz, V. Hatzoglou, Y. Yu, J. Leeman, U. Mahmood, M. Pouryahya, A. Iyer, A. Shukla-Dave, A. Tannenbaum, N. Lee, J. Deasy

This paper develops a network-based method to identify reproducible radiomic features across different imaging settings and validates it using phantom and external datasets.

bioRxiv · Sep 19, 2019 · PreprintBiophysics

Multi-dimensional genomic analysis of myoepithelial carcinoma identifies prevalent oncogenic gene fusions

M. Dalin, N. Katabi, M. Persson, K.-W. Lee, V. Makarov, A. Desrichard, L. Walsh, L. West, Z. Nadeem, D. Ramaswami, J. Havel, F. Kuo, K. Chadalavada, G. Nanjangud, N. Riaz, , L. G. T. Morris

This study identifies prevalent oncogenic gene fusions in myoepithelial carcinoma through genomic analysis, highlighting TGFBR3-PLAG1 as a key fusion and potential therapeutic target.

bioRxiv · Jun 9, 2017Cancer Biology