Computational Biology

Overview

Salk Institute for Biological Studies - Computational Biology - Overview

Overview


To better understand the fundamental “rules” that guide human health and disease, Salk scientists are integrating experimental biology and computational tools, including information theory, computer science, and engineering. The beauty of these approaches is that they can be applied to find patterns in any type of research: cancer, immunology, metabolism, neuroscience, aging, plant biology, and more.

Research


Artificial Intelligence

The field of artificial intelligence (AI) is dedicated to designing machines and algorithms capable of perceiving, understanding, and learning from vast datasets. At Salk, researchers employ AI techniques, such as machine learning and deep learning, to decipher genetic information and refine cancer diagnostics, among other goals, improving their AI models in the process.

Eiman Azim, PhD

Associate Professor

Molecular Neurobiology Laboratory

Margarita Behrens, PhD

Research Professor

Computational Neurobiology Laboratory

Sreekanth Chalasani, PhD

Professor

Molecular Neurobiology Laboratory

Joseph Ecker, PhD

Professor

Genomic Analysis Laboratory, Plant Molecular and Cellular Biology Laboratory

Director, Genomic Analysis Laboratory

Pallav Kosuri, PhD

Assistant Professor

Integrative Biology Laboratory

Dmitry Lyumkis, PhD

Associate Professor

Laboratory of Genetics

Graham McVicker, PhD

Associate Professor

Integrative Biology Laboratory, Laboratory of Genetics

Laboratory of Genetics

Axel Nimmerjahn, PhD

Professor

Waitt Advanced Biophotonics Center

Satchidananda Panda, PhD

Professor

Regulatory Biology Laboratory

John Reynolds, PhD

Professor

Systems Neurobiology Laboratory

Terrence Sejnowski, PhD

Professor and Laboratory Head

Computational Neurobiology Laboratory

Kay Tye, PhD

Professor

Systems Neurobiology Laboratory