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Gherman Novakovsky

6PUBLICATIONS
39CO-AUTHORS
Gene expression (incl. microarray and other genome-wide approaches)Deep learningApplied immunology (incl. antibody engineering, xenotransplantation and t-cell therapies)Cancer therapy (excl. chemotherapy and radiation therapy)
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Publications (6)

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|May 29, 2025
Predicting expression-altering promoter mutations with deep learning.

Kishore Jaganathan, Nicole Ersaro, Gherman Novakovsky

|Jun 27, 2023
ExplaiNN: interpretable and transparent neural networks for genomics.

Gherman Novakovsky, Oriol Fornes, Manu Saraswat

|Mar 27, 2023
Tonic-signaling chimeric antigen receptors drive human regulatory T cell exhaustion.

Caroline Lamarche, Kirsten Ward-Hartstonge, Tian Mi

|Oct 03, 2022
Obtaining genetics insights from deep learning via explainable artificial intelligence.

Gherman Novakovsky, Nick Dexter, Maxwell W Libbrecht

|Sep 28, 2021
Biologically relevant transfer learning improves transcription factor binding prediction.

Gherman Novakovsky, Manu Saraswat, Oriol Fornes

|Aug 21, 2020
Functional effects of chimeric antigen receptor co-receptor signaling domains in human regulatory T cells.

Nicholas A J Dawson, Isaac Rosado-Sánchez, German E Novakovsky

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Frequent Collaborators

3 joint publications

Wyeth W Wasserman

3 joint publications

Sara Mostafavi

2 joint publications

Megan K Levings

2 joint publications

Manu Saraswat

2 joint publications

Oriol Fornes

1 joint publications

Nicholas A J Dawson

1 joint publications

Isaac Rosado-Sánchez

1 joint publications

Vivian C W Fung

1 joint publications

Paul C Orban

1 joint publications

Caroline Lamarche

Frequent Collaborators

3 joint publications

Wyeth W Wasserman

3 joint publications

Sara Mostafavi

2 joint publications

Megan K Levings

2 joint publications

Manu Saraswat

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