Peter K. Koo

Biochemistry, Genetics and Molecular Biology

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 5%percentile

0.447Author DataRank

Indexed papers

2in 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 2 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 →

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

Learning single-cell chromatin accessibility profiles using meta-analytic marker genes

Briefings in Bioinformatics(2022)10.1093/bib/bbac541

Top 54%

0.315DataRank

Top 54%4 citations

Ziqi Tang, Stephan Fischer, Chandana Rajesh, Rohit Tripathy, Peter K. Koo +2 more

Papers

Driven by 33 papers — median percentile 38. Top paper: “WASP family proteins regulate the mobility of the B cell receptor during signaling activation”.

WASP family proteins regulate the mobility of the B cell receptor during signaling activation

Nature Communications(2020)10.1038/s41467-020-14335-8

N/A

0.574DataRank · unranked

45 citations

Brittany A. Wheatley, Peter K. Koo, Anshuman Bhanja, Zhou Shu, S. G. J. Mochrie +4 more

Single Layers of Attention Suffice to Predict Protein Contacts

bioRxiv (Cold Spring Harbor Laboratory)(2020)10.1101/2020.12.21.423882

N/A

0.538DataRank · unranked

35 citations

Neil Thomas, Roshan Rao, Justas Dauparas, Peter K. Koo, David Baker +3 more

Evaluating deep learning for predicting epigenomic profiles

bioRxiv (Cold Spring Harbor Laboratory)(2022)10.1101/2022.04.29.490059

N/A

0.416DataRank · unranked

15 citations

Ziqi Tang, Peter K. Koo, Shushan Toneyan

The structure-fitness landscape of pairwise relations in generative sequence models

bioRxiv (Cold Spring Harbor Laboratory)(2020)10.1101/2020.11.29.402875

N/A

0.330DataRank · unranked

8 citations

Haobo Wang, Michael A. Stiffler, Justas Dauparas, Peter K. Koo, Sergey Ovchinnikov +1 more

Learning single-cell chromatin accessibility profiles using meta-analytic marker genes

Briefings in Bioinformatics(2022)10.1093/bib/bbac541

Top 54%

0.315DataRank

Top 54%4 citations

Ziqi Tang, Stephan Fischer, Chandana Rajesh, Rohit Tripathy, Peter K. Koo +2 more

Massive experimental quantification of amyloid nucleation allows interpretable deep learning of protein aggregation

bioRxiv (Cold Spring Harbor Laboratory)(2024)10.1101/2024.07.13.603366

N/A

0.269DataRank · unranked

5 citations

Mariano Martín, Trinidad Sanmartín Olmo, Chandana Rajesh, Peter K. Koo, Benedetta Bolognesi +2 more

Analysis of single-cell CRISPR perturbations indicates that enhancers act multiplicatively and provides limited evidence for epistatic-like interactions

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.04.26.538501

N/A

0.269DataRank · unranked

5 citations

Karthik Guruvayurappan, Shushan Toneyan, Hsiuyi V. Chen, Aaron R. Chen, Peter K. Koo +2 more

ResidualBind: Uncovering Sequence-Structure Preferences of RNA-Binding Proteins with Deep Neural Networks

Methods in molecular biology(2023)10.1007/978-1-0716-2768-6_12

N/A

0.165DataRank · unranked

2 citations

Matt Ploenzke, Praveen Anand, Steffan B. Paul, Antonio Majdandzic, Peter K. Koo

Learning single-cell chromatin accessibility profiles using meta-analytic marker genes

bioRxiv (Cold Spring Harbor Laboratory)(2021)10.1101/2021.04.01.438068

Top 71%

0.132DataRank

Top 71%1 citations

Ziqi Tang, Stephan Fischer, Chandana Rajesh, Rohit Tripathy, Peter K. Koo +2 more

Light and temperature regulate m 6 A-RNA modification to regulate growth in plants

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.01.17.524395

N/A

0.122DataRank · unranked

1 citations

Amanda Ackermann, Laura Taylor, Peter K. Koo, Ullas V. Pedmale, Oliver Artz

ChampKit: A framework for rapid evaluation of deep neural networks for patch-based histopathology classification

Computer Methods and Programs in Biomedicine(2023)10.1016/j.cmpb.2023.107631

N/A

0DataRank · unranked

16 citations

Rajarsi Gupta, Tahsin Kurç, Shahira Abousamra, Joel Saltz, Peter K. Koo +1 more

Interpreting cis -regulatory mechanisms from genomic deep neural networks using surrogate models

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.11.14.567120

N/A

0DataRank · unranked

11 citations

David M. McCandlish, Justin B. Kinney, Peter K. Koo, E. Seitz

Interpreting Cis -Regulatory Interactions from Large-Scale Deep Neural Networks for Genomics

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.07.03.547592

N/A

0DataRank · unranked

4 citations

Peter K. Koo, Shushan Toneyan

Interpreting cis-regulatory mechanisms from genomic deep neural networks using surrogate models

Nature Machine Intelligence(2024)10.1038/s42256-024-00851-5

N/A

0DataRank · unranked

28 citations

David M. McCandlish, Justin B. Kinney, Peter K. Koo, E. Seitz

Interpreting cis-regulatory interactions from large-scale deep neural networks

Nature Genetics(2024)10.1038/s41588-024-01923-3

N/A

0DataRank · unranked

24 citations

Peter K. Koo, Shushan Toneyan

Analysis of single-cell CRISPR perturbations indicates that enhancers predominantly act multiplicatively

Cell Genomics(2024)10.1016/j.xgen.2024.100672

N/A

0DataRank · unranked

5 citations

Karthik Guruvayurappan, Shushan Toneyan, Hsiuyi V. Chen, Aaron R. Chen, Peter K. Koo +2 more

EvoAug-TF: extending evolution-inspired data augmentations for genomic deep learning to TensorFlow

Bioinformatics(2024)10.1093/bioinformatics/btae092

N/A

0DataRank · unranked

3 citations

Shivani Muthukumar, Peter K. Koo, Yiyang Yu

Evaluating the representational power of pre-trained DNA language models for regulatory genomics

bioRxiv (Cold Spring Harbor Laboratory)(2024)10.1101/2024.02.29.582810

N/A

0DataRank · unranked

26 citations

Nirali Somia, Yiyang Yu, Peter K. Koo, Ziqi Tang

EvoAug-TF: Extending evolution-inspired data augmentations for genomic deep learning to TensorFlow

bioRxiv (Cold Spring Harbor Laboratory)(2024)10.1101/2024.01.17.575961

N/A

0DataRank · unranked

0 citations

Shivani Muthukumar, Peter K. Koo, Yiyang Yu

Probabilistic and machine-learning methods for predicting local rates of transcription elongation from nascent RNA sequencing data

Nucleic Acids Research(2025)10.1093/nar/gkaf092

N/A

0DataRank · unranked

3 citations

Yixin Zhao, R. P. Hassett, Shushan Toneyan, Peter K. Koo, Adam Siepel +1 more

Uncovering the Mechanistic Landscape of Regulatory DNA with Deep Learning

bioRxiv (Cold Spring Harbor Laboratory)(2025)10.1101/2025.10.07.681052

N/A

0DataRank · unranked

3 citations

David M. McCandlish, Justin B. Kinney, Peter K. Koo, E. Seitz

Reusable specimen-level inference in computational pathology

PubMed(2025)10.48550/arxiv.2501.05945

N/A

0DataRank · unranked

0 citations

Sharma, Rishul, Peter K. Koo, Joel Saltz, Jakub Kaczmarzyk

Deep learning for inferring transcription factor binding sites

Current Opinion in Systems Biology(2020)10.1016/j.coisb.2020.04.001

N/A

0DataRank · unranked

79 citations

Matt Ploenzke, Peter K. Koo

eLife Assessment: Generative modeling for RNA splicing predictions and design

(2025)10.7554/elife.106043.1.sa3

N/A

0DataRank · unranked

0 citations

Peter K. Koo

Global Importance Analysis: An Interpretability Method to Quantify Importance of Genomic Features in Deep Neural Networks

bioRxiv (Cold Spring Harbor Laboratory)(2020)10.1101/2020.09.08.288068

N/A

0DataRank · unranked

3 citations

Antonio Majdandzic, Matthew Ploenzke, Praveen Anand, Steffan B. Paul, Peter K. Koo

Global importance analysis: An interpretability method to quantify importance of genomic features in deep neural networks

PLoS Computational Biology(2021)10.1371/journal.pcbi.1008925

N/A

0DataRank · unranked

97 citations

Antonio Majdandzic, Matthew Ploenzke, Praveen Anand, Steffan B. Paul, Peter K. Koo

Evaluating deep learning for predicting epigenomic profiles

Nature Machine Intelligence(2022)10.1038/s42256-022-00570-9

N/A

0DataRank · unranked

70 citations

Ziqi Tang, Peter K. Koo, Shushan Toneyan

End-to-end learning of multiple sequence alignments with differentiable Smith–Waterman

Bioinformatics(2022)10.1093/bioinformatics/btac724

N/A

0DataRank · unranked

44 citations

Nicholas Bhattacharya, Roshan Rao, Justas Dauparas, Neil Thomas, Juannan Zhou +4 more

EvoAug: improving generalization and interpretability of genomic deep neural networks with evolution-inspired data augmentations

bioRxiv (Cold Spring Harbor Laboratory)(2022)10.1101/2022.11.03.515117

N/A

0DataRank · unranked

2 citations

Ziqi Tang, Shushan Toneyan, Peter K. Koo, Nicholas Keone Lee

Correcting gradient-based interpretations of deep neural networks for genomics

bioRxiv (Cold Spring Harbor Laboratory)(2022)10.1101/2022.04.29.490102

N/A

0DataRank · unranked

1 citations

Chandana Rajesh, Peter K. Koo, Antonio Majdandzic

Correcting gradient-based interpretations of deep neural networks for genomics

Genome biology(2023)10.1186/s13059-023-02956-3

N/A

0DataRank · unranked

52 citations

Chandana Rajesh, Peter K. Koo, Antonio Majdandzic

EvoAug: improving generalization and interpretability of genomic deep neural networks with evolution-inspired data augmentations

Genome biology(2023)10.1186/s13059-023-02941-w

N/A

0DataRank · unranked

39 citations

Ziqi Tang, Shushan Toneyan, Peter K. Koo, Nicholas Keone Lee

ETV6 dependency in Ewing sarcoma by antagonism of EWS-FLI1-mediated enhancer activation

Nature Cell Biology(2023)10.1038/s41556-022-01060-1

N/A

0DataRank · unranked

34 citations

Xue‐Yan He, Xiaoli Wu, Yuhan Huang, Shushan Toneyan, Taehoon Ha +7 more

Peter K. Koo

Indexed papers

Top data-sharing exemplar

Papers