Tyler Borrman

5.2k total citations
10 papers, 396 citations indexed

About

Tyler Borrman is a scholar working on Molecular Biology, Oncology and Computational Theory and Mathematics. According to data from OpenAlex, Tyler Borrman has authored 10 papers receiving a total of 396 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 2 papers in Oncology and 2 papers in Computational Theory and Mathematics. Recurrent topics in Tyler Borrman's work include Genomics and Chromatin Dynamics (5 papers), vaccines and immunoinformatics approaches (2 papers) and Protein Structure and Dynamics (2 papers). Tyler Borrman is often cited by papers focused on Genomics and Chromatin Dynamics (5 papers), vaccines and immunoinformatics approaches (2 papers) and Protein Structure and Dynamics (2 papers). Tyler Borrman collaborates with scholars based in United States, Canada and China. Tyler Borrman's co-authors include Zhiping Weng, Brian M. Baker, Nick Rhind, John Bechhoefer, Brian G. Pierce, Shankar Das, Job Dekker, Houda Belaghzal, Denis L. J. Lafontaine and Andrew D. Stephens and has published in prestigious journals such as Nature Genetics, SHILAP Revista de lepidopterología and Molecular Cell.

In The Last Decade

Tyler Borrman

10 papers receiving 390 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tyler Borrman United States	10	323	96	62	58	36	10	396
Ariel Erijman Israel	9	392 1.2×	20 0.2×	51 0.8×	44 0.8×	30 0.8×	11	465
Sheng Qu China	4	422 1.3×	51 0.5×	39 0.6×	30 0.5×	28 0.8×	8	482
Young Joo Sun United States	11	211 0.7×	34 0.4×	34 0.5×	53 0.9×	16 0.4×	28	351
Tomer Tsaban Israel	6	278 0.9×	42 0.4×	61 1.0×	32 0.6×	8 0.2×	7	357
Shubha Suresh United States	5	292 0.9×	42 0.4×	31 0.5×	29 0.5×	10 0.3×	5	396
Ilana L. Stroke United States	12	362 1.1×	79 0.8×	90 1.5×	44 0.8×	51 1.4×	17	506
P. Schutz Sweden	7	562 1.7×	71 0.7×	96 1.5×	11 0.2×	18 0.5×	7	640
Evelyn Plets Belgium	10	275 0.9×	79 0.8×	70 1.1×	49 0.8×	8 0.2×	13	477
Åsa Pérez-Bercoff Sweden	11	293 0.9×	27 0.3×	18 0.3×	16 0.3×	25 0.7×	12	377
G. Y. Srinivasarao United States	9	341 1.1×	43 0.4×	24 0.4×	25 0.4×	10 0.3×	9	426

Countries citing papers authored by Tyler Borrman

Since Specialization

Citations

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

Fields of papers citing papers by Tyler Borrman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tyler Borrman

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

Wang, Weitao, Kyle N. Klein, Karel Proesmans, et al.. (2021). Genome-wide mapping of human DNA replication by optical replication mapping supports a stochastic model of eukaryotic replication. Molecular Cell. 81(14). 2975–2988.e6. 67 indexed citations

Belaghzal, Houda, Tyler Borrman, Andrew D. Stephens, et al.. (2021). Liquid chromatin Hi-C characterizes compartment-dependent chromatin interaction dynamics. Nature Genetics. 53(3). 367–378. 76 indexed citations

Vreven, Thom, et al.. (2020). Performance of ZDOCK and IRAD in CAPRI rounds 39‐45. Proteins Structure Function and Bioinformatics. 88(8). 1050–1054. 12 indexed citations

Borrman, Tyler, Brian G. Pierce, Thom Vreven, Brian M. Baker, & Zhiping Weng. (2020). High-throughput modeling and scoring of TCR-pMHC complexes to predict cross-reactive peptides. Bioinformatics. 36(22-23). 5377–5385. 15 indexed citations

Rajarajan, Prashanth, Tyler Borrman, Will Liao, et al.. (2019). Spatial genome exploration in the context of cognitive and neurological disease. Current Opinion in Neurobiology. 59. 112–119. 10 indexed citations

Borrman, Tyler, et al.. (2017). ATLAS: A database linking binding affinities with structures for wild-type and mutant TCR-pMHC complexes. Proteins Structure Function and Bioinformatics. 85(5). 908–916. 59 indexed citations

Singh, Nishant K., et al.. (2017). Emerging Concepts in TCR Specificity: Rationalizing and (Maybe) Predicting Outcomes. The Journal of Immunology. 199(7). 2203–2213. 61 indexed citations

Vreven, Thom, Brian G. Pierce, Tyler Borrman, & Zhiping Weng. (2016). Performance of ZDOCK and IRAD in CAPRI rounds 28–34. Proteins Structure Function and Bioinformatics. 85(3). 408–416. 14 indexed citations

Das, Shankar, et al.. (2015). Replication timing is regulated by the number of MCMs loaded at origins. Genome Research. 25(12). 1886–1892. 69 indexed citations

10.

Arsuaga, Javier, et al.. (2015). Identification of Copy Number Aberrations in Breast Cancer Subtypes Using Persistence Topology. SHILAP Revista de lepidopterología. 4(3). 339–369. 13 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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