H. Tomas Rube

1.9k total citations
18 papers, 1.1k citations indexed

About

H. Tomas Rube is a scholar working on Molecular Biology, Genetics and Biotechnology. According to data from OpenAlex, H. Tomas Rube has authored 18 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 3 papers in Genetics and 3 papers in Biotechnology. Recurrent topics in H. Tomas Rube's work include RNA and protein synthesis mechanisms (8 papers), Genomics and Chromatin Dynamics (8 papers) and RNA Research and Splicing (7 papers). H. Tomas Rube is often cited by papers focused on RNA and protein synthesis mechanisms (8 papers), Genomics and Chromatin Dynamics (8 papers) and RNA Research and Splicing (7 papers). H. Tomas Rube collaborates with scholars based in United States, Portugal and United Kingdom. H. Tomas Rube's co-authors include Jun S. Song, J Costello, Robert J.A. Bell, Andrew Mancini, Harmen J. Bussemaker, Bruno M. Costa, Ana Xavier‐Magalhães, Chaitanya Rastogi, Sua Myong and Alex Kreig and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

H. Tomas Rube

17 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
H. Tomas Rube United States	14	810	223	146	134	125	18	1.1k
Duanduan Ma United States	17	1.1k 1.3×	74 0.3×	110 0.8×	211 1.6×	459 3.7×	28	1.6k
Victoria Hill United States	17	729 0.9×	102 0.5×	86 0.6×	220 1.6×	338 2.7×	23	1.2k
Lisa S. Westerberg Sweden	23	441 0.5×	122 0.5×	256 1.8×	71 0.5×	303 2.4×	69	1.6k
Kaori Takai United States	16	1.3k 1.6×	625 2.8×	78 0.5×	236 1.8×	225 1.8×	21	1.5k
Yaser Atlasi Netherlands	16	1.3k 1.6×	42 0.2×	106 0.7×	212 1.6×	288 2.3×	29	1.5k
A. Grande-García Spain	12	1.1k 1.4×	190 0.9×	47 0.3×	302 2.3×	522 4.2×	13	2.1k
Trisha Norton Tanzania	18	841 1.0×	88 0.4×	145 1.0×	141 1.1×	366 2.9×	29	2.0k
Brenda O’Connell United States	15	1.4k 1.7×	80 0.4×	156 1.1×	292 2.2×	480 3.8×	21	1.7k
Dana N. Levasseur United States	16	1.9k 2.3×	76 0.3×	399 2.7×	130 1.0×	245 2.0×	21	2.2k
Eugene Ke United States	10	785 1.0×	48 0.2×	127 0.9×	280 2.1×	285 2.3×	20	1.2k

Countries citing papers authored by H. Tomas Rube

Since Specialization

Citations

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

Fields of papers citing papers by H. Tomas Rube

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by H. Tomas Rube. 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 H. Tomas Rube. The network helps show where H. Tomas Rube may publish in the future.

Co-authorship network of co-authors of H. Tomas Rube

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

All Works

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18 of 18 papers shown

Rube, H. Tomas, et al.. (2025). Accurate affinity models for SH2 domains from peptide binding assays and free‐energy regression. Protein Science. 34(11). e70317–e70317.

Guo, Jimmy K., Mario R. Blanco, Isabel N. Goronzy, et al.. (2025). SPIDR enables multiplexed mapping of RNA-protein interactions and uncovers a mechanism for selective translational suppression upon cell stress. Cell. 188(19). 5384–5402.e25. 3 indexed citations

Zhang, Liyang, Gen Li, Yingxiao Zhang, et al.. (2023). Boosting genome editing efficiency in human cells and plants with novel LbCas12a variants. Genome biology. 24(1). 102–102. 30 indexed citations

Rastogi, Chaitanya, Ryan Loker, William J. Glassford, et al.. (2022). Transcription factor paralogs orchestrate alternative gene regulatory networks by context-dependent cooperation with multiple cofactors. Nature Communications. 13(1). 3808–3808. 23 indexed citations

Rube, H. Tomas, Chaitanya Rastogi, Judith F. Kribelbauer, et al.. (2022). Prediction of protein–ligand binding affinity from sequencing data with interpretable machine learning. Nature Biotechnology. 40(10). 1520–1527. 65 indexed citations

Zhang, Liyang, H. Tomas Rube, Christopher A. Vakulskas, et al.. (2020). Systematic in vitro profiling of off-target affinity, cleavage and efficiency for CRISPR enzymes. Nucleic Acids Research. 48(9). 5037–5053. 31 indexed citations

Kribelbauer, Judith F., Ryan Loker, Chaitanya Rastogi, et al.. (2020). Context-Dependent Gene Regulation by Homeodomain Transcription Factor Complexes Revealed by Shape-Readout Deficient Proteins. Molecular Cell. 78(1). 152–167.e11. 19 indexed citations

Basu, Aakash, Dmitriy G. Bobrovnikov, Tunc Kayikcioglu, et al.. (2020). Measuring DNA mechanics on the genome scale. Nature. 589(7842). 462–467. 92 indexed citations

Rube, H. Tomas, Chaitanya Rastogi, Judith F. Kribelbauer, & Harmen J. Bussemaker. (2018). A unified approach for quantifying and interpreting DNA shape readout by transcription factors. Molecular Systems Biology. 14(2). e7902–e7902. 28 indexed citations

10.

Rastogi, Chaitanya, H. Tomas Rube, Judith F. Kribelbauer, et al.. (2018). Accurate and sensitive quantification of protein-DNA binding affinity. Proceedings of the National Academy of Sciences. 115(16). E3692–E3701. 78 indexed citations

11.

Zhang, Liyang, H. Tomas Rube, Judith F. Kribelbauer, et al.. (2017). SelexGLM differentiates androgen and glucocorticoid receptor DNA-binding preference over an extended binding site. Genome Research. 28(1). 111–121. 29 indexed citations

12.

Jin, Hu, H. Tomas Rube, & Jun S. Song. (2016). Categorical spectral analysis of periodicity in nucleosomal DNA. Nucleic Acids Research. 44(5). 2047–2057. 19 indexed citations

13.

Rube, H. Tomas, Wooje Lee, Miroslav Hejna, et al.. (2016). Sequence features accurately predict genome-wide MeCP2 binding in vivo. Nature Communications. 7(1). 11025–11025. 46 indexed citations

14.

Kim, Minji, Alex Kreig, Chun‐Ying Lee, et al.. (2016). Quantitative analysis and prediction of G-quadruplex forming sequences in double-stranded DNA. Nucleic Acids Research. 44(10). 4807–4817. 20 indexed citations

15.

Bell, Robert J.A., H. Tomas Rube, Ana Xavier‐Magalhães, et al.. (2016). Understanding TERT Promoter Mutations: A Common Path to Immortality. Molecular Cancer Research. 14(4). 315–323. 207 indexed citations

16.

Bell, Robert J.A., H. Tomas Rube, Alex Kreig, et al.. (2015). The transcription factor GABP selectively binds and activates the mutant TERT promoter in cancer. Science. 348(6238). 1036–1039. 398 indexed citations

17.

Bell, Robert J.A., H. Tomas Rube, Alex Kreig, et al.. (2015). Abstract B12: GABP selectively binds and activates the mutant TERT promoter across multiple cancer types. Cancer Research. 75(23_Supplement). B12–B12. 1 indexed citations

18.

Rube, H. Tomas & Jun S. Song. (2013). Quantifying the role of steric constraints in nucleosome positioning. Nucleic Acids Research. 42(4). 2147–2158. 9 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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