Satwik Rajaram, Ph.D.
Department Lyda Hill Department of Bioinformatics | Center for Alzheimer’s and Neurodegenerative Diseases | Pathology
Graduate Programs Biomedical Engineering, Cancer Biology
Satwik Rajaram is an Assistant Professor in the Lyda Hill Department of Bioinformatics. He holds secondary appointments in the Department of Pathology and the Center for Alzheimer's and Neurodegenerative Diseases.
Dr. Rajaram's formal training is in theoretical physics. During his postdoc, in the joint labs of Drs. Altschuler and Wu (at UTSW and then at UCSF) he explored the implications of cellular heterogeneity, primarily through quantitative microscopy.
At UTSW, his lab focuses on developing biology-guided machine learning analyses to unravel the information in tissue morphology in two broad areas. First, in the context of kidney cancer, the Rajaram Lab connects tumor architecture to underlying molecular state, drug response and tumor evolution. Second, in the context of neurodegenerative tauopathies, the lab uses morphology and spatial distribution of protein aggregates to better stratify diseases and reconcile their classical neuropathology definitions with the emerging understanding based on protein conformations.
- Cancer Evolution
- Digital Pathology
- Intra-Tumor Heterogeneity
- Machine learning applied to tissue images
- Spatial organization of pathological tissue
- Intratumoral resolution of driver gene mutation heterogeneity in renal cancer using deep learning.
- Acosta P, Panwar V, Jarmale V, Christie A, Jasti J, Margulis V, Rakheja D, Cheville J, Leibovich BC, Parker A, Brugarolas J, Kapur P, Rajaram S, Cancer Res 2022 Jun
- Deep learning reveals disease-specific signatures of white matter pathology in tauopathies.
- Vega AR, Chkheidze R, Jarmale V, Shang P, Foong C, Diamond MI, White CL, Rajaram S, Acta Neuropathol Commun 2021 Oct 9 1 170
- Sampling strategies to capture single-cell heterogeneity.
- Rajaram S, Heinrich LE, Gordan JD, Avva J, Bonness KM, Witkiewicz AK, Malter JS, Atreya CE, Warren RS, Wu LF, Altschuler SJ Nat. Methods 2017 Sep
- Ontological analyses reveal clinically-significant clear cell renal cell carcinoma subtypes with convergent evolutionary trajectories into an aggressive type.
- Cai Q, Christie A, Rajaram S, Zhou Q, Araj E, Chintalapati S, Cadeddu J, Margulis V, Pedrosa I, Rakheja D, McKay RM, Brugarolas J, Kapur P, EBioMedicine 2020 01 51 102526
- Combination Therapy Targeting BCL6 and Phospho-STAT3 Defeats Intratumor Heterogeneity in a Subset of Non-Small Cell Lung Cancers.
- Deb D, Rajaram S, Larsen JE, Dospoy PD, Marullo R, Li LS, Avila K, Xue F, Cerchietti L, Minna JD, Altschuler SJ, Wu LF Cancer Res. 2017 Jun 77 11 3070-3081
- Diverse drug-resistance mechanisms can emerge from drug-tolerant cancer persister cells.
- Ramirez M, Rajaram S, Steininger RJ, Osipchuk D, Roth MA, Morinishi LS, Evans L, Ji W, Hsu CH, Thurley K, Wei S, Zhou A, Koduru PR, Posner BA, Wu LF, Altschuler SJ Nat Commun 2016 Feb 7 10690
- On comparing heterogeneity across biomarkers.
- Steininger RJ, Rajaram S, Girard L, Minna JD, Wu LF, Altschuler SJ Cytometry A 2015 Jun 87 6 558-67
- A simple image correction method for high-throughput microscopy.
- Coster AD, Wichaidit C, Rajaram S, Altschuler SJ, Wu LF Nat. Methods 2014 Jun 11 6 602
- Rapid analysis and exploration of fluorescence microscopy images.
- Pavie B, Rajaram S, Ouyang A, Altschuler JM, Steininger RJ, Wu LF, Altschuler SJ J Vis Exp 2014 Mar 85
- PhenoRipper: software for rapidly profiling microscopy images.
- Rajaram S, Pavie B, Wu LF, Altschuler SJ Nat. Methods 2012 Jun 9 7 635-7