Anat Kreimer

2.1k total citations
21 papers, 1.1k citations indexed

About

Anat Kreimer is a scholar working on Molecular Biology, Genetics and Organic Chemistry. According to data from OpenAlex, Anat Kreimer has authored 21 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 5 papers in Genetics and 1 paper in Organic Chemistry. Recurrent topics in Anat Kreimer's work include Genomics and Chromatin Dynamics (10 papers), Bioinformatics and Genomic Networks (7 papers) and RNA Research and Splicing (7 papers). Anat Kreimer is often cited by papers focused on Genomics and Chromatin Dynamics (10 papers), Bioinformatics and Genomic Networks (7 papers) and RNA Research and Splicing (7 papers). Anat Kreimer collaborates with scholars based in United States, Israel and Japan. Anat Kreimer's co-authors include Eytan Ruppin, Uri Gophna, Shiri Freilich, Elhanan Borenstein, Nir Yosef, Nadav Ahituv, Roded Sharan, Tal Ashuach, Fumitaka Inoue and Walter L. Eckalbar and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Anat Kreimer

18 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anat Kreimer United States 13 853 177 172 89 60 21 1.1k
Katrin Bohl Germany 11 480 0.6× 279 1.6× 166 1.0× 60 0.7× 58 1.0× 15 866
Amir Mitchell United States 14 775 0.9× 287 1.6× 92 0.5× 198 2.2× 83 1.4× 20 1.1k
Avihu H. Yona Israel 7 639 0.7× 294 1.7× 87 0.5× 165 1.9× 52 0.9× 8 906
Hélène Auger France 9 833 1.0× 266 1.5× 161 0.9× 139 1.6× 48 0.8× 11 1.3k
Alexandra J. Scott United States 9 781 0.9× 411 2.3× 219 1.3× 161 1.8× 26 0.4× 12 1.2k
Matteo Avella United States 21 300 0.4× 162 0.9× 202 1.2× 38 0.4× 22 0.4× 28 1.8k
Gabriel V. Markov France 20 452 0.5× 251 1.4× 181 1.1× 151 1.7× 44 0.7× 39 998
Michael D. R. Croning United Kingdom 8 777 0.9× 93 0.5× 99 0.6× 176 2.0× 34 0.6× 8 1.2k
Jiao Cheng China 20 455 0.5× 135 0.8× 178 1.0× 133 1.5× 116 1.9× 75 1.2k
Shanshan Liu China 15 464 0.5× 390 2.2× 188 1.1× 157 1.8× 12 0.2× 51 1.1k

Countries citing papers authored by Anat Kreimer

Since Specialization
Citations

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

Fields of papers citing papers by Anat Kreimer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anat Kreimer

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

All Works

20 of 20 papers shown
1.
Zhang, Hanwen, Hong Yan, Qian Yang, et al.. (2025). Mutations of schizophrenia risk gene SETD1A dysregulate synaptic function in human neurons. Molecular Psychiatry. 30(12). 5680–5693.
2.
DeGroat, William, Fumitaka Inoue, Tal Ashuach, et al.. (2024). Comprehensive network modeling approaches unravel dynamic enhancer-promoter interactions across neural differentiation. Genome biology. 25(1). 221–221.
3.
Liu, Jiayi, et al.. (2024). Network Analysis of Enhancer–Promoter Interactions Highlights Cell-Type-Specific Mechanisms of Transcriptional Regulation Variation. International Journal of Molecular Sciences. 25(18). 9840–9840.
4.
Liu, Jiayi, Tal Ashuach, Fumitaka Inoue, et al.. (2024). Optimizing sequence design strategies for perturbation MPRAs: a computational evaluation framework. Nucleic Acids Research. 52(4). 1613–1627. 1 indexed citations
5.
An, Joon‐Yong, et al.. (2023). Characterization of De Novo Promoter Variants in Autism Spectrum Disorder with Massively Parallel Reporter Assays. International Journal of Molecular Sciences. 24(4). 3509–3509. 8 indexed citations
6.
Liu, Jiayi, Anat Kreimer, & Wei Vivian Li. (2023). Differential variability analysis of single-cell gene expression data. Briefings in Bioinformatics. 24(5). 3 indexed citations
7.
Kreimer, Anat, Tal Ashuach, Fumitaka Inoue, et al.. (2022). Massively parallel reporter perturbation assays uncover temporal regulatory architecture during neural differentiation. Nature Communications. 13(1). 1504–1504. 27 indexed citations
8.
Ziffra, Ryan, Chang N. Kim, Jayden Ross, et al.. (2021). Single-cell epigenomics reveals mechanisms of human cortical development. Nature. 598(7879). 205–213. 153 indexed citations
9.
Gordon, M. Grace, Fumitaka Inoue, Beth Martin, et al.. (2020). lentiMPRA and MPRAflow for high-throughput functional characterization of gene regulatory elements. Nature Protocols. 15(8). 2387–2412. 70 indexed citations
10.
Ashuach, Tal, David S. Fischer, Anat Kreimer, et al.. (2019). MPRAnalyze: statistical framework for massively parallel reporter assays. Genome biology. 20(1). 183–183. 53 indexed citations
11.
Inoue, Fumitaka, Anat Kreimer, Tal Ashuach, Nadav Ahituv, & Nir Yosef. (2019). Identification and Massively Parallel Characterization of Regulatory Elements Driving Neural Induction. Cell stem cell. 25(5). 713–727.e10. 72 indexed citations
12.
Eckalbar, Walter L., et al.. (2017). Use antibiotics in cell culture with caution: genome-wide identification of antibiotic-induced changes in gene expression and regulation. Scientific Reports. 7(1). 7533–7533. 82 indexed citations
13.
Levy, Roie, Rogan Carr, Anat Kreimer, Shiri Freilich, & Elhanan Borenstein. (2015). NetCooperate: a network-based tool for inferring host-microbe and microbe-microbe cooperation. BMC Bioinformatics. 16(1). 164–164. 66 indexed citations
14.
Kreimer, Anat & Itsik Pe’er. (2013). Variants in exons and in transcription factors affect gene expression in trans. Genome biology. 14(7). R71–R71. 6 indexed citations
15.
Kreimer, Anat, et al.. (2012). Inference of modules associated to eQTLs. Nucleic Acids Research. 40(13). e98–e98. 9 indexed citations
16.
Kreimer, Anat, Adi Doron‐Faigenboim, Elhanan Borenstein, & Shiri Freilich. (2012). NetCmpt: a network-based tool for calculating the metabolic competition between bacterial species. Bioinformatics. 28(16). 2195–2197. 34 indexed citations
17.
Freilich, Shiri, Anat Kreimer, Elhanan Borenstein, et al.. (2010). Decoupling Environment-Dependent and Independent Genetic Robustness across Bacterial Species. PLoS Computational Biology. 6(2). e1000690–e1000690. 29 indexed citations
18.
Freilich, Shiri, et al.. (2010). The large-scale organization of the bacterial network of ecological co-occurrence interactions. Nucleic Acids Research. 38(12). 3857–3868. 236 indexed citations
19.
Freilich, Shiri, Anat Kreimer, Elhanan Borenstein, et al.. (2009). Metabolic-network-driven analysis of bacterial ecological strategies. Genome biology. 10(6). R61–R61. 82 indexed citations
20.
Kreimer, Anat, Elhanan Borenstein, Uri Gophna, & Eytan Ruppin. (2008). The evolution of modularity in bacterial metabolic networks. Proceedings of the National Academy of Sciences. 105(19). 6976–6981. 146 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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