Nir Atias

1.0k total citations
14 papers, 630 citations indexed

About

Nir Atias is a scholar working on Molecular Biology, Computational Theory and Mathematics and Pharmacology. According to data from OpenAlex, Nir Atias has authored 14 papers receiving a total of 630 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 3 papers in Computational Theory and Mathematics and 2 papers in Pharmacology. Recurrent topics in Nir Atias's work include Bioinformatics and Genomic Networks (8 papers), Microbial Metabolic Engineering and Bioproduction (5 papers) and Computational Drug Discovery Methods (3 papers). Nir Atias is often cited by papers focused on Bioinformatics and Genomic Networks (8 papers), Microbial Metabolic Engineering and Bioproduction (5 papers) and Computational Drug Discovery Methods (3 papers). Nir Atias collaborates with scholars based in Israel, United States and Germany. Nir Atias's co-authors include Roded Sharan, Eytan Ruppin, Assaf Gottlieb, Matthew Oberhardt, Ze’ev Melamed, Gil Ast, Galit Lev-Maor, Asaf Levy, Sebastián Kadener and Martin Kupiec and has published in prestigious journals such as Nucleic Acids Research, Molecular Cell and Bioinformatics.

In The Last Decade

Nir Atias

14 papers receiving 623 citations

Peers

Nir Atias

MB

CTM

CR

PHARM

CB

Ziaurrehman Tanoli Finland

Alfred A. Rabow United States

Jayme Holmes United States

Lewis Mervin United Kingdom

Xichen Lian China

Xinbin Zhao China

Tomohiro Sato Japan

Zi Liu China

Daniel J. Mason United Kingdom

Liliana Halip Romania

Ziaurrehman Tanoli Finland

Nir Atias

541 ×1.1

MB

349 ×1.3

CTM

74 ×0.8

CR

54 ×0.7

PHARM

21 ×0.5

CB

Citations per year, relative to Nir Atias Nir Atias (= 1×) peers Ziaurrehman Tanoli

Countries citing papers authored by Nir Atias

Since Specialization

Citations

This map shows the geographic impact of Nir Atias'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 Nir Atias with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nir Atias more than expected).

Fields of papers citing papers by Nir Atias

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nir Atias. 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 Nir Atias. The network helps show where Nir Atias may publish in the future.

Co-authorship network of co-authors of Nir Atias

This figure shows the co-authorship network connecting the top 25 collaborators of Nir Atias. A scholar is included among the top collaborators of Nir Atias 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 Nir Atias. Nir Atias is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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14 of 14 papers shown

1.

Atias, Nir, et al.. (2017). ANAT 2.0: reconstructing functional protein subnetworks. BMC Bioinformatics. 18(1). 495–495. 9 indexed citations

2.

Hollander, Dror, Maya Donyo, Nir Atias, et al.. (2016). A network-based analysis of colon cancer splicing changes reveals a tumorigenesis-favoring regulatory pathway emanating from ELK1. Genome Research. 26(4). 541–553. 50 indexed citations

3.

Oberhardt, Matthew, et al.. (2016). Metabolic Network Prediction of Drug Side Effects. Cell Systems. 2(3). 209–213. 70 indexed citations

4.

Atias, Nir, Martin Kupiec, & Roded Sharan. (2015). Systematic identification and correction of annotation errors in the genetic interaction map ofSaccharomyces cerevisiae. Nucleic Acids Research. 44(5). e50–e50. 16 indexed citations

5.

Reiterer, Veronika, Francesco Baschieri, Júlia Hoffmann, et al.. (2014). Regulation of Sec16 levels and dynamics links proliferation and secretion. Journal of Cell Science. 128(4). 670–82. 32 indexed citations

6.

Atias, Nir, et al.. (2014). Experimental design schemes for learning Boolean network models. Bioinformatics. 30(17). i445–i452. 9 indexed citations

7.

Atias, Nir & Roded Sharan. (2013). iPoint: an integer programming based algorithm for inferring protein subnetworks. Molecular BioSystems. 9(7). 1662–1669. 10 indexed citations

8.

Atias, Nir, Sorin Istrail, & Roded Sharan. (2013). Pathway-based analysis of genomic variation data. Current Opinion in Genetics & Development. 23(6). 622–626. 6 indexed citations

9.

Melamed, Ze’ev, Asaf Levy, Reut Ashwal-Fluss, et al.. (2013). Alternative Splicing Regulates Biogenesis of miRNAs Located across Exon-Intron Junctions. Molecular Cell. 50(6). 869–881. 81 indexed citations

10.

Gazy, Inbal, Batia Liefshitz, Alex Bronstein, et al.. (2013). A Genetic Screen for High Copy Number Suppressors of the Synthetic Lethality Betweenelg1Δandsrs2Δin Yeast. G3 Genes Genomes Genetics. 3(5). 917–926. 15 indexed citations

11.

Atias, Nir & Roded Sharan. (2012). Comparative analysis of protein networks. Communications of the ACM. 55(5). 88–97. 26 indexed citations

12.

Atias, Nir & Roded Sharan. (2011). An Algorithmic Framework for Predicting Side Effects of Drugs. Journal of Computational Biology. 18(3). 207–218. 102 indexed citations

13.

Gottlieb, Assaf, et al.. (2011). Combining Drug and Gene Similarity Measures for Drug-Target Elucidation. Journal of Computational Biology. 18(2). 133–145. 162 indexed citations

14.

Yosef, Nir, Einat Zalckvar, Assaf D. Rubinstein, et al.. (2011). ANAT: A Tool for Constructing and Analyzing Functional Protein Networks. Science Signaling. 4(196). pl1–pl1. 42 indexed citations

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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