Kourosh Zarringhalam

1.1k total citations
43 papers, 633 citations indexed

About

Kourosh Zarringhalam is a scholar working on Molecular Biology, Artificial Intelligence and Parasitology. According to data from OpenAlex, Kourosh Zarringhalam has authored 43 papers receiving a total of 633 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 8 papers in Artificial Intelligence and 5 papers in Parasitology. Recurrent topics in Kourosh Zarringhalam's work include Gene Regulatory Network Analysis (6 papers), RNA and protein synthesis mechanisms (5 papers) and Gene expression and cancer classification (5 papers). Kourosh Zarringhalam is often cited by papers focused on Gene Regulatory Network Analysis (6 papers), RNA and protein synthesis mechanisms (5 papers) and Gene expression and cancer classification (5 papers). Kourosh Zarringhalam collaborates with scholars based in United States, China and Singapore. Kourosh Zarringhalam's co-authors include Jeffrey H. Chuang, Saman Farahmand, David L. Rimm, Daniel Ziemek, Michelle M. Meyer, Iván Dotú, Peter Clote, Aileen I. Fernandez, Javad Noorbakhsh and Dennis L. Caruana and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Kourosh Zarringhalam

42 papers receiving 625 citations

Peers

Countries citing papers authored by Kourosh Zarringhalam

Since Specialization

Citations

This map shows the geographic impact of Kourosh Zarringhalam's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kourosh Zarringhalam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kourosh Zarringhalam more than expected).

Fields of papers citing papers by Kourosh Zarringhalam

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kourosh Zarringhalam. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kourosh Zarringhalam. The network helps show where Kourosh Zarringhalam may publish in the future.

Co-authorship network of co-authors of Kourosh Zarringhalam

This figure shows the co-authorship network connecting the top 25 collaborators of Kourosh Zarringhalam. A scholar is included among the top collaborators of Kourosh Zarringhalam based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kourosh Zarringhalam. Kourosh Zarringhalam is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Heterogeneous Responses to High-Dose Testosterone in Castration-Resistant Prostate Cancer Tumors with Mixed Rb-Proficient and Rb-Deficient Cells 2025 ·Molecular Cancer Therapeutics ·(unknown), Wanting Han, (unknown), (unknown), Nancy Patten, (unknown), Susan Patalano, Jill A. Macoska, Steven P. Balk, Dong Han, Kourosh Zarringhalam, Changmeng Cai	0
2	Single cell expression and chromatin accessibility of the Toxoplasma gondii lytic cycle identifies AP2XII-8 as an essential ribosome regulon driver 2024 ·Nature Communications ·(unknown), (unknown), (unknown), (unknown), (unknown), David Degras, (unknown), Manoj T. Duraisingh, Kourosh Zarringhalam, Marc‐Jan Gubbels	4
3	Comparative chemical genomics in Babesia species identifies the alkaline phosphatase PhoD as a determinant of antiparasitic resistance 2024 ·Proceedings of the National Academy of Sciences ·(unknown), Brendan Elsworth, Jacob A. Tennessen, Aditya S. Paul, (unknown), (unknown), (unknown), (unknown), Marvin J. Meyers, Kourosh Zarringhalam, Manoj T. Duraisingh	1
4	A Bayesian noisy logic model for inference of transcription factor activity from single cell and bulk transcriptomic data 2023 ·NAR Genomics and Bioinformatics ·(unknown), Susan Patalano, Jill A. Macoska, Kourosh Zarringhalam	2
5	Comparative single-cell transcriptional atlases of Babesia species reveal conserved and species-specific expression profiles 2022 ·PLoS Biology ·(unknown), (unknown), Brendan Elsworth, (unknown), Marc‐Jan Gubbels, Manoj T. Duraisingh, Kourosh Zarringhalam	11
6	Susceptibility-Associated Genetic Variation in NEDD9 Contributes to Prostate Cancer Initiation and Progression 2021 ·Cancer Research ·Dong Han, (unknown), (unknown), (unknown), (unknown), (unknown), Susan Patalano, Shuai Gao, (unknown), Jill A. Macoska, Kourosh Zarringhalam, Kellee R. Siegfried, Xin Yuan, Timothy R. Rebbeck, Changmeng Cai	4
7	Deep learning trained on hematoxylin and eosin tumor region of Interest predicts HER2 status and trastuzumab treatment response in HER2+ breast cancer 2021 ·Modern Pathology ·Saman Farahmand, Aileen I. Fernandez, (unknown), David L. Rimm, Jeffrey H. Chuang, Emily Reisenbichler, Kourosh Zarringhalam	97
8	Deep learning-based cross-classifications reveal conserved spatial behaviors within tumor histological images 2020 ·Nature Communications ·Javad Noorbakhsh, Saman Farahmand, Ali Foroughi pour, Sandeep Namburi, Dennis L. Caruana, David L. Rimm, (unknown), Kourosh Zarringhalam, Jeffrey H. Chuang	124
9	Patch-DCA: improved protein interface prediction by utilizing structural information and clustering DCA scores 2019 ·Bioinformatics ·Amir Vajdi, Kourosh Zarringhalam, Nurit Haspel	9
10	Causal Inference Engine: a platform for directional gene set enrichment analysis and inference of active transcriptional regulators 2019 ·Nucleic Acids Research ·Saman Farahmand, (unknown), Jill A. Macoska, Kourosh Zarringhalam	8
11	ModEx: A text mining system for extracting mode of regulation of transcription factor-gene regulatory interaction 2019 ·Journal of Biomedical Informatics ·Saman Farahmand, Todd Riley, Kourosh Zarringhalam	8
12	Robust phenotype prediction from gene expression data using differential shrinkage of co-regulated genes 2018 ·Scientific Reports ·Kourosh Zarringhalam, David Degras, (unknown), Daniel Ziemek	15
13	Prediction of bacterial small RNAs in the RsmA (CsrA) and ToxT pathways: a machine learning approach 2017 ·BMC Genomics ·(unknown), (unknown), Ping Chen, Rahul Kulkarni, Kourosh Zarringhalam	11
14	A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data 2017 ·BMC Bioinformatics ·(unknown), Wei Ding, Luoyan Zhang, Daniel Ziemek, Kourosh Zarringhalam	26
15	Identification of competing endogenous RNAs of the tumor suppressor gene PTEN: A probabilistic approach 2017 ·Scientific Reports ·Kourosh Zarringhalam, Yvonne Tay, (unknown), Assaf C. Bester, Pier Paolo Pandolfi, Rahul Kulkarni	17
16	Interpreting transcriptional changes using causal graphs: new methods and their practical utility on public networks 2016 ·BMC Bioinformatics ·(unknown), (unknown), Alex Gutteridge, Ben S. Sidders, Ping Chen, Daniel Ziemek, Kourosh Zarringhalam	26
17	Pressure dependency of localization degree in heavy fermion CeIn3: A density functional theory analysis 2016 ·Scientific Reports ·(unknown), S. Jalali-Asadabadi, Iftikhar Ahmad, Kourosh Zarringhalam	13
18	Dynamics of the Ethanolamine Glycerophospholipid Remodeling Network 2012 ·PLoS ONE ·Lu Zhang, (unknown), Kourosh Zarringhalam, Martin Hermansson, Pentti Somerharju, Jeffrey H. Chuang	12
19	An open system for automatic home-cage behavioral analysis and its application to male and female mouse models of Huntington's disease 2012 ·Behavioural Brain Research ·Kourosh Zarringhalam, Minhan Ka, (unknown), Joseph I. Terranova, Yongjoon Suh, Oliver D. King, Moonkyoung Um	21
20	Integrating Chemical Footprinting Data into RNA Secondary Structure Prediction 2012 ·PLoS ONE ·Kourosh Zarringhalam, Michelle M. Meyer, Iván Dotú, Jeffrey H. Chuang, Peter Clote	74

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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