Jake Lever

3.4k total citations · 2 hit papers
22 papers, 2.1k citations indexed

About

Jake Lever is a scholar working on Molecular Biology, Artificial Intelligence and Genetics. According to data from OpenAlex, Jake Lever has authored 22 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 5 papers in Artificial Intelligence and 2 papers in Genetics. Recurrent topics in Jake Lever's work include Biomedical Text Mining and Ontologies (10 papers), Bioinformatics and Genomic Networks (7 papers) and Topic Modeling (3 papers). Jake Lever is often cited by papers focused on Biomedical Text Mining and Ontologies (10 papers), Bioinformatics and Genomic Networks (7 papers) and Topic Modeling (3 papers). Jake Lever collaborates with scholars based in Canada, United States and United Kingdom. Jake Lever's co-authors include Martin Krzywinski, Naomi Altman, Steven J.M. Jones, Martin Jones, Jasleen Grewal, Eric Y. Stutheit-Zhao, Russ B. Altman, Dixie L. Mager, Mohammad M. Karimi and Artem Babaian and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Bioinformatics and Nature Methods.

In The Last Decade

Jake Lever

21 papers receiving 2.1k citations

Hit 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.

Principal component analysis

2017 943 citations Jake Lever, Martin Krzywinski et al. Nature Methods profile →
Model selection and overfitting

2016 469 citations Jake Lever, Martin Krzywinski et al. Nature Methods profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jake Lever Canada	13	539	328	153	122	109	22	2.1k
D. Wang China	35	633 1.2×	399 1.2×	319 2.1×	155 1.3×	101 0.9×	186	4.0k
Xia Wang China	29	432 0.8×	185 0.6×	207 1.4×	60 0.5×	72 0.7×	215	3.0k
Ricardo Cao Spain	29	394 0.7×	429 1.3×	159 1.0×	162 1.3×	63 0.6×	164	2.6k
Skipper Seabold United States	3	493 0.9×	373 1.1×	154 1.0×	141 1.2×	62 0.6×	5	3.5k
Li Ma China	30	366 0.7×	579 1.8×	250 1.6×	125 1.0×	62 0.6×	169	4.6k
Josef Perktold United States	3	493 0.9×	373 1.1×	154 1.0×	144 1.2×	62 0.6×	3	3.5k
Laura Toloşi Germany	6	258 0.5×	391 1.2×	73 0.5×	68 0.6×	50 0.5×	10	2.0k
Yufei Chen China	29	543 1.0×	319 1.0×	262 1.7×	166 1.4×	123 1.1×	176	2.8k
Ajit C. Tamhane United States	31	375 0.7×	456 1.4×	96 0.6×	164 1.3×	68 0.6×	121	5.3k
Michel Lang Germany	14	263 0.5×	545 1.7×	71 0.5×	68 0.6×	59 0.5×	39	1.7k

Countries citing papers authored by Jake Lever

Since Specialization

Citations

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

Fields of papers citing papers by Jake Lever

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jake Lever

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Hintzen, Rogier, Alex de Giorgio, Julien Fauqueur, et al.. (2023). Associating biological context with protein-protein interactions through text mining at PubMed scale. Journal of Biomedical Informatics. 145. 104474–104474. 1 indexed citations

2.

Lever, Jake & Russ B. Altman. (2021). Analyzing the vast coronavirus literature with CoronaCentral. Proceedings of the National Academy of Sciences. 118(23). 17 indexed citations

3.

Chen, Binbin, Amit Kaushal, Adam Lavertu, et al.. (2021). Repurposing biomedical informaticians for COVID-19. Journal of Biomedical Informatics. 115. 103673–103673. 1 indexed citations

4.

Lever, Jake, et al.. (2021). Search and visualization of gene-drug-disease interactions for pharmacogenomics and precision medicine research using GeneDive. Journal of Biomedical Informatics. 117. 103732–103732. 5 indexed citations

5.

Lever, Jake, et al.. (2020). Extending TextAE for annotation of non-contiguous entities. Genomics & Informatics. 18(2). e15–e15. 2 indexed citations

6.

Babaian, Artem, I. Richard Thompson, Jake Lever, et al.. (2019). LIONS: analysis suite for detecting and quantifying transposable element initiated transcription from RNA-seq. Bioinformatics. 35(19). 3839–3841. 21 indexed citations

7.

Lever, Jake, Eric Y. Stutheit-Zhao, Jasleen Grewal, Martin Jones, & Steven J.M. Jones. (2019). CancerMine: a literature-mined resource for drivers, oncogenes and tumor suppressors in cancer. Nature Methods. 16(6). 505–507. 121 indexed citations

8.

Lever, Jake, Martin Jones, Arpad Danos, et al.. (2019). Text-mining clinically relevant cancer biomarkers for curation into the CIViC database. Genome Medicine. 11(1). 78–78. 25 indexed citations

9.

Lever, Jake, Julia M. Barbarino, Li Gong, et al.. (2019). PGxMine: Text mining for curation of PharmGKB. PubMed. 25. 611–622. 12 indexed citations

10.

Lee, Jessica J. Y., Jake Lever, Steven J.M. Jones, et al.. (2018). Text‐based phenotypic profiles incorporating biochemical phenotypes of inborn errors of metabolism improve phenomics‐based diagnosis. Journal of Inherited Metabolic Disease. 41(3). 555–562. 3 indexed citations

11.

Lever, Jake, Sitanshu Gakkhar, Michael C. Gottlieb, et al.. (2017). A collaborative filtering-based approach to biomedical knowledge discovery. Bioinformatics. 34(4). 652–659. 21 indexed citations

12.

Lever, Jake, Martin Krzywinski, & Naomi Altman. (2017). Principal component analysis. Nature Methods. 14(7). 641–642. 943 indexed citations breakdown →

13.

Lever, Jake & Steven J.M. Jones. (2017). Painless Relation Extraction with Kindred. 176–183. 6 indexed citations

14.

Lever, Jake, Martin Krzywinski, & Naomi Altman. (2016). Model selection and overfitting. Nature Methods. 13(9). 703–704. 469 indexed citations breakdown →

15.

Lever, Jake, Martin Jones, & Steven J.M. Jones. (2016). CancerMine: Knowledge Base Construction for Personalised Cancer Treatment. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 1 indexed citations

16.

Grinshtein, Natalie, Richard Marcellus, David Uehling, et al.. (2016). Small molecule epigenetic screen identifies novel EZH2 and HDAC inhibitors that target glioblastoma brain tumor-initiating cells. Oncotarget. 7(37). 59360–59376. 30 indexed citations

17.

Lever, Jake, Martin Krzywinski, & Naomi Altman. (2016). Logistic regression. Nature Methods. 13(7). 541–542. 95 indexed citations

18.

Lever, Jake & Steven J.M. Jones. (2016). VERSE: Event and Relation Extraction in the BioNLP 2016 Shared Task. 42–49. 26 indexed citations

19.

Lever, Jake, Martin Krzywinski, & Naomi Altman. (2016). Regularization. Nature Methods. 13(10). 803–804. 34 indexed citations

20.

Lever, Jake & Taku Komura. (2012). Real-time controllable fire using textured forces. The Visual Computer. 28(6-8). 691–700. 6 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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