Genomics and Computational Biology

Computational biology generally involves the development of theoretical models algorithmic tools, and their application to biological data, in order to gain novel biological understanding regarding biological, ecological, behavioral, and social systems.

The use of mathematical modeling and computational inference tools allows researchers to analyze large quantities of biological data and make quantitative predictions, providing an otherwise inaccessible understanding of the system at hand.

Researchers in this field:

Prof. Lilach Hadany

Our lab investigates open questions in the theory of evolution, and plant bioacoustics.

Evolutionary theory projects include the evolution of genetic variation, social behavior, host-microbiome interactions, language, and aging.

Plant bioacoustics projects include plant sound emission, interpretation of plant sounds, and plant responses to the sounds of animals and plants.

Lab capabilities: Mathematical modeling of evolutionary processes; plant recording; analysis of plant sounds

Services to the industry: none    

Lab Website: https://www.hadanylab.com/

Prof. Itay Mayrose

The lab of Prof. Itay Mayrose specializes in computational biology and bioinformatics, with an emphasis on plant evolution and genomics. We use computational tools to gain insights into the fascinating evolutionary dynamics of plant genomes. In this process, we develop novel computational tools based on machine learning, reinforcement learning, and advanced probabilistic evolutionary models. Current projects in the lab include: (1) Whole genome duplications (polyploidy): Studying the consequences of whole genome duplications on patterns of lineage diversification, biogeography, and the effects of polyploidy on evolutionary patterns at the molecular and genomic levels. (2) Genome editing: We develop novel tools and algorithms for the optimal design of genome editing experiments and how to apply them in a large-scale manner, with special emphasis on crop improvement. (3) Phylogenetics: We develop machine learning methods for more accurate inference of phylogenetic trees and evolutionary genomic analyses.

Lab Website: https://www.tau.ac.il/~itaymay/index.html

Dr. Yasmine Meroz

 The lab studies computational and behavioral processes in plants; how plants process sensory information about the environment in order to shape their growth morphology. We study processes such as active sensing, decision-making, memory phenomena, and interaction between plants. Our research combines both theory and experiment. As part of our experiments we design and build tailored experimental setups with the aim of interrogating how plants integrate sensory information over space and time, with an image analysis pipeline.  Experiments are generally informed by predictions of mathematical models and numerical frameworks, including 3D simulations of plant growth (tropisms and circumnutations), concepts from control theory and physics, the interplay with mechanics, and cost-benefit models.    

Lab Website: https://www.merozlab.com/