Our research is focused on three areas: 1) Integration of genomic and functional genomics data to formulate biological hypotheses for human disease-related processes. 2) Understanding complex human diseases through structure, dynamics and function of disease-related networks. 3) Genetic robustness or fail-safe mechanisms engineered to genetic networks. Using data-mining, statistics approaches and network theories, we first try to generate biological hypotheses and computational models, and then use molecular biology, cell biology and systems biology approaches to validate and refine models and hypotheses.

Prof. Gerwert heads the Department of Biophysics, which focus its studies on proteins, their mechanisms and interactions in networks, especially on membrane and membrane bound proteins which are involved in diseases.

The Computational Regulatory Genomics Department was established in Fall 2006 under the direction of PICB interim director Prof. Dr. Martin Vingron. Regulatory Genomics refers to studies of gene regulation, signal transduction, and gene networks that are based on genomic sequences and on large-scale functional-genomics data.

Prof. Li JIN 's group of Genetics and Bioinformatics, aims to examine the molecular evolution of human populations and to identify the genetic basis of complex human diseases.

Group of Phylogenetic Combinatorics

We study how proteins and other biomacromolecules function by investigating their mechanics, dynamics and evolution.

Proteins and RNA are constantly perturbed by their environment by external stimuli such as binding partners, by mechanical force, and by changes in pH, temperature and other factors.

These perturbations are the basic elements of the information curcuits in the cell. Examples are allosteric enzymes, modifications of natively unfolded proteins, or proteins under mechanical stress.

Our group uses molecular simulations, mainly atomic-detail Molecular Dynamics simulations, in combination with evolutionary analyses to decipher how proteins are regulated by and function upon perturbations.

We aim at explaining and predicting the molecular basis of communication in cells, in signalling cascades and throughout larger protein assemblies, to investigate how it might be modified for new purposes.

We (Laboratory of Evolutionary Genomics) are focusing on two following topics: 1) Locating the genes involved in the adaptation to environmental changes in the recent past in model species (human, Drosophila, mouse and Arabidopsis ). It is of great interest to study further the regulatory regions that regulate genes acting in the nervous system. Such work will provide insights into the intricate nature of human evolution. 2) Theoretical population genetics and bioinformatics studies. We develop methods to test evolutionary hypothesis, and study population structure and genomic comparison.

Molecular mechanisms of human development and aging ("Molecular Lifespan" project). Molecular physiology of the human brain and evolution of human-specific features. Evolution of gene expression regulation.

Computational Biology Algorithm Design Comparative Genomics Pattern Discovery

Translational research represents a novel approach to life sciences with the specific goal to enhance and accelerate their applications in healthcare. In particular, it focuses on multi-disciplinary collaboration among life sciences, exact sciences. and medicine, with the aim of advancing molecular-based medicine. In fact, it aims to enable physicians to leverage systems- and computational-biology approaches to allow early detection of complex diseases, increase efficiency in drug development and therapy testing, improve drug efficacy, and enable personalized medicine. Such an approach is necessary to narrow the gap existing between clinical practice and basic research, to accelerate the bidirectional flow of scientific discoveries into the clinic and of clinical findings into novel research directions, and to realize the (crucial !) return on investment made by private and public institutions on life science basic research. Our group contributes to this vision with research on two families of diseases, metabolic and immune syndromes that appear to be ultimately intertwined via the disruption of the immune system. More ...

Our major research interest is to look for functional human genetic variations and to understand their biological mechanism and evolutionary roles. Genetically, People differ from each other by hundred thousands of small genetic variations. A small fraction of these genetic variations affect function. They make us a phenotypically very diverse species. Such phenotype diversity occurs among populations, such as skin pigmentation and lactose tolerance in adulthood etc.; and also between individuals, such as stature, weight, psychological tendency and drug metabolism. To understand these functional genetic variations, two strategies are to be applied. The first is to detect and characterize evidences of positive selection. The second strategy is to use association related approaches.

Functional Genomics workgroup is focusing on large-scale computational analysis of high-throughput genomic data to understand the molecular mechanism involved in complex physiological processes such as animal hibernation and circadian rhythm. In the past, we have successfully applied computational and statistical methods to identify the differentially expressed genes and key functional pathways during animal hibernation. Currently, we are developing computational methods to combine literature information, gene expression data, and promoter sequence data to construct gene regulatory networks for mammalian circadian rhythm. In the future, we will develop novel algorithms to analyze complex biological networks to identify functional modules and compare different networks. We will also use mathematical modeling and computer simulation to study the complex dynamics of these biological networks.

Signal Transduction and Biosystems

Plant System Biology

The goal of the Population Genomics Group (PGG) is to understand the evolutionary dynamics of genomes at population level using computational approaches, and to bridge evolutionary history and genomic medicine. Currently, PGG is focusing on analysis of genetic structure, inference of human genetic history, detection of natural selection, mapping genes underlying complex diseases in human populations, and identifying the differentially expressed genes among populations. A new focus is to study allele-allele interaction and gene-gene interaction in recent admixture populations.

Our laboratory is to understand RNA regulatory networks in higher eukaryotes at the whole transcriptome level by taking advantage of state-of-the-art deep sequencing approaches and computational analyses. Currently, there are two major research areas: one is to decipher alternative splicing networks in model organism Drosophila melanogaster (fruitfly) and the other is to discover new modes of gene regulation and new noncoding RNA species in human embryonic stem cells and their specific differentiation lineages. By using both molecular and computational biology approaches, our study will have profound impacts on the understanding of RNA complexity and its functions in higher eukaryotes.

Epigenetic mechanisms play critical roles in regulating cellular differentiation. Histone modifications are implicated in regulating gene expression by controlling chromatin structure and DNA accessibility. Our research focuses on how chromatin structure, especially histone modification patterns are established during cellular differentiation process and how they contribute to normal development and disease states. With the technique of next-generation sequencing, we will be able to address these questions systematically and gain interesting insights into the relationship between epigenetic modifications and gene transcription.

Specific aim 1: To understand how transcription factors and chromatin regulators regulate the target genes through modulating histone modifications.

Specific aim 2: To understand how long-range chromatin interactions are regulated and contribute to epigenetic and transcriptional regulation.

Specific aim 3: To identify novel lineage specific enhancers and transcription factors in genome-wide.