Igor Ulitsky

20.8k total citations · 8 hit papers
94 papers, 11.2k citations indexed

About

Igor Ulitsky is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Igor Ulitsky has authored 94 papers receiving a total of 11.2k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Molecular Biology, 51 papers in Cancer Research and 4 papers in Genetics. Recurrent topics in Igor Ulitsky's work include Cancer-related molecular mechanisms research (43 papers), RNA Research and Splicing (41 papers) and RNA modifications and cancer (35 papers). Igor Ulitsky is often cited by papers focused on Cancer-related molecular mechanisms research (43 papers), RNA Research and Splicing (41 papers) and RNA modifications and cancer (35 papers). Igor Ulitsky collaborates with scholars based in Israel, United States and Germany. Igor Ulitsky's co-authors include David P. Bartel, Ron Shamir, Noa Gil, Roded Sharan, Alena Shkumatava, Calvin H. Jan, Hazel Sive, Yoav Lubelsky, Rotem Ben‐Tov Perry and David Koppstein and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Igor Ulitsky

90 papers receiving 11.0k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

lincRNAs: Genomics, Evolution, and Mechanisms

2013 2.1k citations Igor Ulitsky, David P. Bartel profile →
Conserved Function of lincRNAs in Vertebrate Embryonic Development despite Rapid Sequence Evolution

2011 932 citations Igor Ulitsky, David P. Bartel et al. profile →
Network‐based prediction of protein function

2007 764 citations Igor Ulitsky, Ron Shamir et al. Molecular Systems Biology profile →
Circular RNAs are long-lived and display only minimal early alterations in response to a growth factor

2015 535 citations Igor Ulitsky et al. Nucleic Acids Research profile →
Regulation of gene expression by cis-acting long non-coding RNAs

2019 502 citations Noa Gil, Igor Ulitsky profile →
Principles of Long Noncoding RNA Evolution Derived from Direct Comparison of Transcriptomes in 17 Species

2015 463 citations David P. Bartel, Igor Ulitsky et al. Cell Reports profile →
Evolution to the rescue: using comparative genomics to understand long non-coding RNAs

2016 384 citations Igor Ulitsky profile →
SARS-CoV-2 uses a multipronged strategy to impede host protein synthesis

2021 160 citations Yaara Finkel, Aharon Nachshon et al. Nature profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Igor Ulitsky Israel	48	9.5k	6.6k	587	557	513	94	11.2k
Or Zuk Israel	22	6.4k 0.7×	4.7k 0.7×	1.7k 3.0×	595 1.1×	230 0.4×	38	8.9k
Moran N. Cabili United States	14	7.1k 0.7×	5.8k 0.9×	608 1.0×	335 0.6×	432 0.8×	17	8.2k
Rolf Backofen Germany	52	9.0k 1.0×	1.4k 0.2×	1.6k 2.8×	392 0.7×	322 0.6×	274	10.7k
Stijn van Dongen United Kingdom	24	6.9k 0.7×	5.2k 0.8×	568 1.0×	953 1.7×	71 0.1×	35	9.6k
Manuel Ares United States	56	11.3k 1.2×	1.5k 0.2×	831 1.4×	456 0.8×	117 0.2×	126	13.2k
Paul Bertone United States	48	10.4k 1.1×	1.9k 0.3×	1.1k 1.8×	598 1.1×	81 0.2×	68	12.0k
Albin Sandelin Denmark	48	11.8k 1.2×	2.7k 0.4×	2.0k 3.5×	1.0k 1.9×	145 0.3×	108	14.5k
Saeed Tavazoie United States	38	7.7k 0.8×	1.1k 0.2×	1.5k 2.5×	448 0.8×	184 0.4×	71	9.3k
Zhenyu Xuan United States	36	7.7k 0.8×	4.0k 0.6×	1.3k 2.3×	392 0.7×	88 0.2×	85	9.4k
Alberto Pascual-Montano Spain	30	3.7k 0.4×	1.6k 0.2×	425 0.7×	560 1.0×	107 0.2×	49	5.2k

Countries citing papers authored by Igor Ulitsky

Since Specialization

Citations

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

Fields of papers citing papers by Igor Ulitsky

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Igor Ulitsky

This figure shows the co-authorship network connecting the top 25 collaborators of Igor Ulitsky. A scholar is included among the top collaborators of Igor Ulitsky 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 Igor Ulitsky. Igor Ulitsky 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

Römer, Christine, M A Strauch, B. M. Zuckerman, et al.. (2025). Neuromuscular dysfunction in patient-derived FUSR244RR–ALS iPSC model via axonal downregulation of neuromuscular junction proteins. PubMed. 2(2). ugaf005–ugaf005.

Ziv, Omer, Rotem Ben‐Tov Perry, Yoav Lubelsky, et al.. (2024). Structural features within the NORAD long noncoding RNA underlie efficient repression of Pumilio activity. Nature Structural & Molecular Biology. 32(2). 287–299. 4 indexed citations

Yang, Li, Igor Ulitsky, Wendy V. Gilbert, et al.. (2024). The challenges of investigating RNA function. Molecular Cell. 84(19). 3567–3571. 3 indexed citations

Lödige, Inga, et al.. (2023). Massively parallel identification of mRNA localization elements in primary cortical neurons. Nature Neuroscience. 26(3). 394–405. 23 indexed citations

Gil, Noa, Rotem Ben‐Tov Perry, Zohar Mukamel, et al.. (2023). Complex regulation of Eomes levels mediated through distinct functional features of the Meteor long non-coding RNA locus. Cell Reports. 42(6). 112569–112569. 5 indexed citations

Perry, Rotem Ben‐Tov, et al.. (2023). Silc1 long noncoding RNA is an immediate-early gene promoting efficient memory formation. Cell Reports. 42(10). 113168–113168. 8 indexed citations

Ulitsky, Igor, et al.. (2022). Unique features of transcription termination and initiation at closely spaced tandem human genes. Molecular Systems Biology. 18(4). e10682–e10682. 3 indexed citations

Dubois, Agnès, Inma González, Noa Gil, et al.. (2022). OCT4 activates a Suv39h1 -repressive antisense lncRNA to couple histone H3 Lysine 9 methylation to pluripotency. Nucleic Acids Research. 50(13). 7367–7379. 8 indexed citations

Pai, Balagopal, Rohit Menon, Anna Bludau, et al.. (2022). Transcriptome and chromatin alterations in social fear indicate association of MEG3 with successful extinction of fear. Molecular Psychiatry. 27(10). 4064–4076. 7 indexed citations

10.

Slobodin, Boris, B. M. Zuckerman, Amir Ben‐Shmuel, et al.. (2022). Cap-independent translation and a precisely located RNA sequence enable SARS-CoV-2 to control host translation and escape anti-viral response. Nucleic Acids Research. 50(14). 8080–8092. 26 indexed citations

11.

Finkel, Yaara, Aharon Nachshon, Roni Winkler, et al.. (2021). SARS-CoV-2 uses a multipronged strategy to impede host protein synthesis. Nature. 594(7862). 240–245. 160 indexed citations breakdown →

12.

Lubelsky, Yoav, et al.. (2021). Highly conserved and cis-acting lncRNAs produced from paralogous regions in the center of HOXA and HOXB clusters in the endoderm lineage. PLoS Genetics. 17(7). e1009681–e1009681. 13 indexed citations

13.

Lubelsky, Yoav, B. M. Zuckerman, & Igor Ulitsky. (2021). High‐resolution mapping of function and protein binding in an RNA nuclear enrichment sequence. The EMBO Journal. 40(12). e106357–e106357. 12 indexed citations

14.

Taiber, Shahar, Likhitha Kolla, Ran Elkon, et al.. (2020). Identification and characterization of key long non-coding RNAs in the mouse cochlea. RNA Biology. 18(8). 1160–1169. 7 indexed citations

15.

Zuckerman, B. M., et al.. (2020). Gene Architecture and Sequence Composition Underpin Selective Dependency of Nuclear Export of Long RNAs on NXF1 and the TREX Complex. Molecular Cell. 79(2). 251–267.e6. 96 indexed citations

16.

Arandkar, Sharathchandra, Noa Furth, Nishanth Belugali Nataraj, et al.. (2018). Altered p53 functionality in cancer-associated fibroblasts contributes to their cancer-supporting features. Proceedings of the National Academy of Sciences. 115(25). 6410–6415. 93 indexed citations

17.

Haimon, Zhana, Johannes Orthgieß, Sigalit Boura‐Halfon, et al.. (2018). Re-evaluating microglia expression profiles using RiboTag and cell isolation strategies. Nature Immunology. 19(6). 636–644. 141 indexed citations

18.

Ulitsky, Igor, et al.. (2015). Methods for distinguishing between protein-coding and long noncoding RNAs and the elusive biological purpose of translation of long noncoding RNAs. Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms. 1859(1). 31–40. 70 indexed citations

19.

Auyeung, Vincent C., Igor Ulitsky, Sean E. McGeary, & David P. Bartel. (2013). Beyond Secondary Structure: Primary-Sequence Determinants License Pri-miRNA Hairpins for Processing. DSpace@MIT (Massachusetts Institute of Technology). 11 indexed citations

20.

Linhart, Chaim, et al.. (2009). Allegro: Analyzing expression and sequence in concert to discover regulatory programs. Nucleic Acids Research. 37(5). 1566–1579. 34 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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