🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Michał Bryliński

Louisiana State University

ORCID: 0000-0002-6204-2869
Biochemistry, Genetics and Molecular BiologyComputer ScienceEngineering

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 4%percentile
0.927Author DataRank

Indexed papers

3in pilot corpus
datarank_citation_only_1hop_v6· scope data_onlyMethodology
Why this DataRank?

An author's DataRank is the sum of the DataRanks of all 3 indexed papers attributed to them. A prolific author with many moderate-impact papers can outrank one with a single high-impact paper.

Author scores recompute whenever paper DataRanks are refreshed, so this number lags the underlying paper scores by at most one batch run.

Read the full methodology →

Top data-sharing exemplar

The highest-impact dataset this researcher has shared, ranked by DataRank — the single contribution doing the most to lift their data-sharing standing.

An integrated network representation of multiple cancer-specific data for graph-based machine learning

npj Systems Biology and Applications(2022)10.1038/s41540-022-00226-9
Top 45%
0.414DataRank
Top 45%9 citations

Manali Singha, Hsiao‐Chun Wu, Costas Busch, J. Ramanujam, Michał Bryliński +1 more

Papers

Driven by 13 papers — median percentile 54. Top paper: “An integrated network representation of multiple cancer-specific data for graph-based machine learning”.

An integrated network representation of multiple cancer-specific data for graph-based machine learning

npj Systems Biology and Applications(2022)10.1038/s41540-022-00226-9
Top 45%
0.414DataRank
Top 45%9 citations

Manali Singha, Hsiao‐Chun Wu, Costas Busch, J. Ramanujam, Michał Bryliński +1 more

Augmented drug combination dataset to improve the performance of machine learning models predicting synergistic anticancer effects

Scientific Reports(2024)10.1038/s41598-024-51940-9
Top 46%
0.403DataRank
Top 46%9 citations

Gopal Srivastava, J. Ramanujam, Michał Bryliński, Mengmeng Liu

Augmented drug combination dataset to improve the performance of machine learning models predicting synergistic anticancer effects

Research Square(2023)10.21203/rs.3.rs-3481858/v1
Top 72%
0.109DataRank
Top 72%1 citations

Gopal Srivast, J. Ramanujam, Michał Bryliński, Mengmeng Liu

GraphDTI: A robust deep learning predictor of drug-target interactions from multiple heterogeneous data

Journal of Cheminformatics(2021)10.1186/s13321-021-00540-0
N/A
0DataRank · unranked
28 citations

Manali Singha, Limeng Pu, Prasanga Neupane, Joseph Feinstein, Hsiao‐Chun Wu +3 more

Exploring the Effects of Genetic Variation on Gene Regulation in Cancer in the Context of 3D Genome Structure

Civil War Book Review(2021)10.21203/rs.3.rs-496328/v1
N/A
0DataRank · unranked
0 citations

Abd-El-Monsif Shawky, Michał Bryliński, Noha M. Osman

CancerOmicsNet: a multi-omics network-based approach to anti-cancer drug profiling

Oncotarget(2022)10.18632/oncotarget.28234
N/A
0DataRank · unranked
26 citations

Manali Singha, J. Ramanujam, Michał Bryliński, Limeng Pu

BionoiNet: ligand-binding site classification with off-the-shelf deep neural network

Bioinformatics(2020)10.1093/bioinformatics/btaa094
N/A
0DataRank · unranked
15 citations

Jeffrey Lemoine, Abd-El-Monsif Shawky, Manali Singha, Limeng Pu, Shuangyan Yang +3 more

Pocket2Drug: An Encoder-Decoder Deep Neural Network for the Target-Based Drug Design

Frontiers in Pharmacology(2022)10.3389/fphar.2022.837715
N/A
0DataRank · unranked
20 citations

Manali Singha, Gopal Srivastava, Limeng Pu, J. Ramanujam, Michał Bryliński +1 more

Artificial intelligence to guide precision anticancer therapy with multitargeted kinase inhibitors

BMC Cancer(2022)10.1186/s12885-022-10293-0
N/A
0DataRank · unranked
14 citations

Limeng Pu, Brent Stanfield, Ifeanyi K. Uche, Paul J. F. Rider, Konstantin G. Kousoulas +3 more

Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure

BMC Genomic Data(2022)10.1186/s12863-021-01021-x
N/A
0DataRank · unranked
11 citations

Abd-El-Monsif Shawky, Michał Bryliński, Noha M. Osman

GraphSite: Ligand Binding Site Classification with Deep Graph Learning

Biomolecules(2022)10.3390/biom12081053
N/A
0DataRank · unranked
25 citations

Manali Singha, Limeng Pu, Gopal Srivastava, J. Ramanujam, Michał Bryliński +1 more

GraphGR: A graph neural network to predict the effect of pharmacotherapy on the cancer cell growth

bioRxiv (Cold Spring Harbor Laboratory)(2020)10.1101/2020.05.20.107458
N/A
0DataRank · unranked
9 citations

Limeng Pu, Abd-El-Monsif Shawky, Konstantin Busch, Hsiao‐Chun Wu, J. Ramanujam +2 more

Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure

bioRxiv (Cold Spring Harbor Laboratory)(2020)10.1101/2020.10.06.328567
N/A
0DataRank · unranked
0 citations

Abd-El-Monsif Shawky, Michał Bryliński, Noha M. Osman