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Satwik Rajaram

6PUBLICATIONS

21CO-AUTHORS

Proteomics and metabolomicsMolecular targetsDeep learningCentral nervous systemPredictive and prognostic markers

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Publications (6)

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|Dec 18, 2025

Resolving phenotyping discordance with SPACEMAP, an integrated machine learning framework.

Bassel Dawod, Arely Perez Rodriguez, Sebastian Diegeler

|Mar 18, 2025

Histopathology based AI model predicts anti-angiogenic therapy response in renal cancer clinical trial.

Jay Jasti, Hua Zhong, Vandana Panwar

|Jun 02, 2022

Intratumoral Resolution of Driver Gene Mutation Heterogeneity in Renal Cancer Using Deep Learning.

Paul H Acosta, Vandana Panwar, Vipul Jarmale

|Oct 22, 2021

Deep learning reveals disease-specific signatures of white matter pathology in tauopathies.

Anthony R Vega, Rati Chkheidze, Vipul Jarmale

|Nov 02, 2019

A multi-modal data resource for investigating topographic heterogeneity in patient-derived xenograft tumors.

Satwik Rajaram, Maike A Roth, Julia Malato

|Sep 05, 2017

Sampling strategies to capture single-cell heterogeneity.

Satwik Rajaram, Louise E Heinrich, John D Gordan

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Frequent Collaborators

2 joint publications

Steven J Altschuler

2 joint publications

Payal Kapur

2 joint publications

Paul H Acosta

2 joint publications

Vipul Jarmale

2 joint publications

Dinesh Rakheja

2 joint publications

James Brugarolas

1 joint publications

Louise E Heinrich

1 joint publications

Maike A Roth

1 joint publications

Todd A Aguilera

1 joint publications

Rati Chkheidze

Frequent Collaborators

2 joint publications

Steven J Altschuler

2 joint publications

Payal Kapur

2 joint publications

Paul H Acosta

2 joint publications

Vipul Jarmale

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