Gherman Novakovsky

1.4k total citations · 1 hit paper
9 papers, 421 citations indexed

About

Gherman Novakovsky is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Gherman Novakovsky has authored 9 papers receiving a total of 421 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 2 papers in Oncology and 2 papers in Immunology. Recurrent topics in Gherman Novakovsky's work include CAR-T cell therapy research (2 papers), ATP Synthase and ATPases Research (2 papers) and T-cell and B-cell Immunology (2 papers). Gherman Novakovsky is often cited by papers focused on CAR-T cell therapy research (2 papers), ATP Synthase and ATPases Research (2 papers) and T-cell and B-cell Immunology (2 papers). Gherman Novakovsky collaborates with scholars based in Canada, United States and Germany. Gherman Novakovsky's co-authors include Sara Mostafavi, Wyeth W. Wasserman, Nick Dexter, Maxwell W. Libbrecht, Megan K. Levings, Qing Huang, Oriol Fornés, Manu Saraswat, Isaac Rosado‐Sánchez and Majid Mojibian and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Reviews Genetics and Genome biology.

In The Last Decade

Gherman Novakovsky

9 papers receiving 415 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.

Obtaining genetics insights from deep learning via explainable artificial intelligence

2022 185 citations Gherman Novakovsky, Nick Dexter et al. Nature Reviews Genetics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gherman Novakovsky Canada	8	196	104	102	54	42	9	421
Lujia Chen United States	12	359 1.8×	43 0.4×	85 0.8×	37 0.7×	72 1.7×	36	603
Taylor E. Arnoff United States	6	172 0.9×	28 0.3×	73 0.7×	72 1.3×	15 0.4×	10	336
Alexander Tong United States	10	180 0.9×	78 0.8×	82 0.8×	28 0.5×	27 0.6×	31	320
Diana Thomas United States	11	90 0.5×	79 0.8×	147 1.4×	37 0.7×	100 2.4×	24	345
Cody N. Heiser United States	7	143 0.7×	45 0.4×	60 0.6×	25 0.5×	14 0.3×	13	241
Lương Hữu Đăng Vietnam	11	102 0.5×	52 0.5×	31 0.3×	30 0.6×	48 1.1×	24	383
Alexandra So United States	3	106 0.5×	31 0.3×	55 0.5×	21 0.4×	16 0.4×	3	273
Sai Batchu United States	10	89 0.5×	81 0.8×	47 0.5×	36 0.7×	10 0.2×	49	332
Chandler Gatenbee United States	12	236 1.2×	143 1.4×	137 1.3×	18 0.3×	79 1.9×	16	548
Jen‐Yeu Wang United States	11	175 0.9×	15 0.1×	65 0.6×	30 0.6×	19 0.5×	22	399

Countries citing papers authored by Gherman Novakovsky

Since Specialization

Citations

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

Fields of papers citing papers by Gherman Novakovsky

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gherman Novakovsky

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

All Works

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9 of 9 papers shown

1.

Novakovsky, Gherman, Oriol Fornés, Manu Saraswat, Sara Mostafavi, & Wyeth W. Wasserman. (2023). ExplaiNN: interpretable and transparent neural networks for genomics. Genome biology. 24(1). 154–154. 23 indexed citations

2.

Novakovsky, Gherman, Shugo Sasaki, Oriol Fornés, et al.. (2023). In silico discovery of small molecules for efficient stem cell differentiation into definitive endoderm. Stem Cell Reports. 18(3). 765–781. 9 indexed citations

3.

Lamarche, Caroline, Kirsten A. Ward‐Hartstonge, Mi Tian, et al.. (2023). Tonic-signaling chimeric antigen receptors drive human regulatory T cell exhaustion. Proceedings of the National Academy of Sciences. 120(14). e2219086120–e2219086120. 37 indexed citations

4.

Novakovsky, Gherman, Nick Dexter, Maxwell W. Libbrecht, Wyeth W. Wasserman, & Sara Mostafavi. (2022). Obtaining genetics insights from deep learning via explainable artificial intelligence. Nature Reviews Genetics. 24(2). 125–137. 185 indexed citations breakdown →

5.

Novakovsky, Gherman, Manu Saraswat, Oriol Fornés, Sara Mostafavi, & Wyeth W. Wasserman. (2021). Biologically relevant transfer learning improves transcription factor binding prediction. Genome biology. 22(1). 280–280. 26 indexed citations

6.

Dawson, Nicholas A.J., Isaac Rosado‐Sánchez, Gherman Novakovsky, et al.. (2020). Functional effects of chimeric antigen receptor co-receptor signaling domains in human regulatory T cells. Science Translational Medicine. 12(557). 100 indexed citations

7.

Babaian, Artem, et al.. (2018). bioSyntax: syntax highlighting for computational biology. BMC Bioinformatics. 19(1). 303–303. 2 indexed citations

8.

Novakovsky, Gherman, Daria V. Dibrova, & Armen Y. Mulkidjanian. (2016). Phylogenomic analysis of type 1 NADH:Quinone oxidoreductase. Biochemistry (Moscow). 81(7). 770–784. 8 indexed citations

9.

Evstafieva, Alexandra G., Alisa A. Garaeva, Anastasia A. Khutornenko, et al.. (2014). A sustained deficiency of mitochondrial respiratory complex III induces an apoptotic cell death through the p53-mediated inhibition of pro-survival activities of the activating transcription factor 4. Cell Death and Disease. 5(11). e1511–e1511. 31 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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