Jacob Schreiber

68 total papers · 3.4k total citations
22 papers, 1.2k citations indexed

About

Jacob Schreiber is a scholar working on Molecular Biology, Biomedical Engineering and Artificial Intelligence. According to data from OpenAlex, Jacob Schreiber has authored 22 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 4 papers in Biomedical Engineering and 3 papers in Artificial Intelligence. Recurrent topics in Jacob Schreiber's work include Genomics and Chromatin Dynamics (10 papers), Epigenetics and DNA Methylation (6 papers) and Genomics and Phylogenetic Studies (5 papers). Jacob Schreiber is often cited by papers focused on Genomics and Chromatin Dynamics (10 papers), Epigenetics and DNA Methylation (6 papers) and Genomics and Phylogenetic Studies (5 papers). Jacob Schreiber collaborates with scholars based in United States, Germany and Austria. Jacob Schreiber's co-authors include William Stafford Noble, Mark Akeson, Jay Shendure, Katherine S. Pollard, Sean Whalen, Kevin Karplus, Jeffrey A. Bilmes, Anh Leith, Molly Gasperini and Melissa D. Zhang and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Jacob Schreiber

21 papers receiving 1.2k citations

Hit Papers

A Genome-wide Framework f... 2019 2026 2021 2023 2019 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Jacob Schreiber 980 226 169 77 75 22 1.2k
Ivan Labat 805 0.8× 167 0.7× 89 0.5× 58 0.8× 57 0.8× 17 1.0k
Žaklina Strezoska 1.1k 1.1× 69 0.3× 140 0.8× 76 1.0× 74 1.0× 22 1.3k
Christoph Zechner 1.2k 1.2× 139 0.6× 137 0.8× 56 0.7× 104 1.4× 41 1.4k
Sinem K. Saka 977 1.0× 245 1.1× 49 0.3× 83 1.1× 69 0.9× 19 1.3k
Yiyong Liu 992 1.0× 110 0.5× 108 0.6× 170 2.2× 40 0.5× 49 1.4k
Karen H. Miga 1.0k 1.1× 142 0.6× 375 2.2× 106 1.4× 525 7.0× 15 1.3k
Velia Siciliano 826 0.8× 133 0.6× 152 0.9× 85 1.1× 32 0.4× 31 1.0k
Felix Bestvater 742 0.8× 199 0.9× 87 0.5× 105 1.4× 46 0.6× 43 1.4k
Rachael E. Workman 853 0.9× 130 0.6× 155 0.9× 144 1.9× 146 1.9× 13 1.0k
Yong Fuga Li 563 0.6× 158 0.7× 104 0.6× 54 0.7× 27 0.4× 15 1.1k

Countries citing papers authored by Jacob Schreiber

Since Specialization
Citations

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

Fields of papers citing papers by Jacob Schreiber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jacob Schreiber

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

All Works

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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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