Izhar Wallach

915 total citations
10 papers, 149 citations indexed

About

Izhar Wallach is a scholar working on Computational Theory and Mathematics, Molecular Biology and Epidemiology. According to data from OpenAlex, Izhar Wallach has authored 10 papers receiving a total of 149 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computational Theory and Mathematics, 6 papers in Molecular Biology and 2 papers in Epidemiology. Recurrent topics in Izhar Wallach's work include Computational Drug Discovery Methods (7 papers), Protein Structure and Dynamics (3 papers) and Breastfeeding Practices and Influences (2 papers). Izhar Wallach is often cited by papers focused on Computational Drug Discovery Methods (7 papers), Protein Structure and Dynamics (3 papers) and Breastfeeding Practices and Influences (2 papers). Izhar Wallach collaborates with scholars based in Canada, Australia and Argentina. Izhar Wallach's co-authors include Ryan Lilien, Navdeep Jaitly, Abraham Heifets, Kong T. Nguyen, Facundo García‐Bournissen, Reo Tanoshima, Shinya Ito, Matthieu Schapira, Yusuke Tanigawara and Dongxu Zhai and has published in prestigious journals such as Bioinformatics, PLoS ONE and Science Advances.

In The Last Decade

Izhar Wallach

10 papers receiving 147 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Izhar Wallach Canada	7	94	84	18	18	17	10	149
Oriol Guitart-Pla Spain	6	114 1.2×	137 1.6×	25 1.4×	11 0.6×	24 1.4×	9	189
Eli Fernández‐de Gortari Mexico	10	132 1.4×	174 2.1×	34 1.9×	10 0.6×	29 1.7×	18	278
Briana Foley United States	9	54 0.6×	127 1.5×	9 0.5×	7 0.4×	14 0.8×	18	246
Misha Itkin United States	5	109 1.2×	96 1.1×	15 0.8×	22 1.2×	10 0.6×	6	238
Ricard García-Serna Spain	11	174 1.9×	144 1.7×	51 2.8×	39 2.2×	8 0.5×	15	298
Maicol Bissaro Italy	12	98 1.0×	197 2.3×	27 1.5×	7 0.4×	17 1.0×	18	288
Shuoyan Tan China	8	179 1.9×	227 2.7×	34 1.9×	11 0.6×	50 2.9×	19	343
Gergely Zahoránszky-Köhalmi United States	8	90 1.0×	110 1.3×	21 1.2×	21 1.2×	19 1.1×	13	175
Juan I. Di Filippo Argentina	6	169 1.8×	144 1.7×	14 0.8×	13 0.7×	40 2.4×	6	267
Azedine Zoufir United Kingdom	7	53 0.6×	127 1.5×	11 0.6×	26 1.4×	11 0.6×	10	193

Countries citing papers authored by Izhar Wallach

Since Specialization

Citations

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

Fields of papers citing papers by Izhar Wallach

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Izhar Wallach

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

All Works

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10 of 10 papers shown

Zhai, Dongxu, Le Wang, Ping Su, et al.. (2023). Small-molecule targeting AMPA-mediated excitotoxicity has therapeutic effects in mouse models for multiple sclerosis. Science Advances. 9(49). eadj6187–eadj6187. 9 indexed citations

Tanoshima, Reo, et al.. (2018). Quetiapine Excretion Into Human Breast Milk. Journal of Clinical Psychopharmacology. 38(4). 362–364. 2 indexed citations

Wallach, Izhar & Abraham Heifets. (2017). Most Ligand-Based Benchmarks Measure Overfitting Rather than Accuracy.. 4 indexed citations

Tanoshima, Reo, Facundo García‐Bournissen, Yusuke Tanigawara, et al.. (2014). Population PK modelling and simulation based on fluoxetine and norfluoxetine concentrations in milk: a milk concentration‐based prediction model. British Journal of Clinical Pharmacology. 78(4). 918–928. 12 indexed citations

Wallach, Izhar, Navdeep Jaitly, Kong T. Nguyen, Matthieu Schapira, & Ryan Lilien. (2011). Normalizing Molecular Docking Rankings using Virtually Generated Decoys. Journal of Chemical Information and Modeling. 51(8). 1817–1830. 8 indexed citations

Wallach, Izhar, Navdeep Jaitly, & Ryan Lilien. (2010). A Structure-Based Approach for Mapping Adverse Drug Reactions to the Perturbation of Underlying Biological Pathways. PLoS ONE. 5(8). e12063–e12063. 44 indexed citations

Wallach, Izhar. (2010). Pharmacophore inference and its application to computational drug discovery. Drug Development Research. 72(1). 17–25. 7 indexed citations

Wallach, Izhar & Ryan Lilien. (2009). The protein–small-molecule database, a non-redundant structural resource for the analysis of protein-ligand binding. Bioinformatics. 25(5). 615–620. 38 indexed citations

Wallach, Izhar & Ryan Lilien. (2009). Predicting Multiple Ligand Binding Modes Using Self-Consistent Pharmacophore Hypotheses. Journal of Chemical Information and Modeling. 49(9). 2116–2128. 6 indexed citations

10.

Wallach, Izhar & Ryan Lilien. (2009). Prediction of sub-cavity binding preferences using an adaptive physicochemical structure representation. Bioinformatics. 25(12). i296–i304. 19 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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