Prof. Liran Carmel
My lab deals with a host of topics in the general fields of molecular evolution, computational biology, and genetics. Among the topics that are currently
actively pursued are: Recent human Recent advances in ancient DNA sequencing yielded complete high-coverage evolution genomes of the Neandertal and the Denisovan. My lab is interested in identifying phenotypic differences between these human groups, especially those that are related to cognition. Based on the understanding that many phenotypic differences between closely related species may be attributed to
changes in gene regulation, we devise algorithms that predict the epigenetics of ancient DNA, and that identifies which genes are differently regulated in modern humans and in ancient humans. We identified hundreds of such genes, and initiated a series of experiments to measure the phenotypic effects of some leading candidates. Among them are genes that affect human neuronal development, and we study their effect in mouse models.
We study conservation of gene architecture by means of intronic positional conservation. This is an extension of the more "standard" sequence and
structure evolutionary conservation modes. We are interested in the quantification of this conservation, and in studying its implication on our
understanding of intronic functions. We also study the evolutionary forces that have led to the wealth of gene architectures seen across the eukaryotic domain. This includes the identification of evolutionary trends, and the study of mechanisms of intron gain and loss.
We study the functional roles of splicing in general, and of alternative splicing in particular. We develop a tool to estimate the effect of splicing on normal splicing patterns, and its connection to human diseases.
Nonsense Mediated Decay (NMD)
We are interested in the mechanism that recognizes a premature termination codon in mammals, and its relationship with introns in the 3'UTR. We also study its impact on codon usage bias along genes.
We characterize the dynamics of gene architecture in individual genes, and are interested in studying the connections between this dynamics and other genic features.
My lab is also active in some fields of applied mathematics: multivariate Analysis analysis, statistical pattern recognition, data visualization, and machine learning.