|【July 28】||9:10-||Prof. Akinori Kidera||Abstract||HP|
|【July 28】||14:00-||Prof. Nir Friedman||Abstract||HP|
|【July 29】||9:10-||Prof. Hiroki R. Ueda||Abstract||HP|
|【July 30】||9:10-||Prof. David Landsman||Abstract||HP|
Prof. Akinori Kidera
MULTI-SCALE/MULTI-PHYSICS SIMULATIONS OF PROTEIN FUNCTIONS
Biomolecular functions at the single molecular level can be stated rigorously in physical terms as,
"A series of protein structure changes as a response to an external perturbation such as ligand binding, and accompanying chemical reactions."
A protein function starts with an external perturbation imposed on the protein system. The response to the perturbation initiates the relaxation process to a new equilibrium structure, resulting in a structural change in the protein. The structural change accompanies a chemical reaction in the ligand molecule, converting it into a product. The product molecule and/or the protein in the new equilibrium structure in turn become the perturbation for another protein system. This process can occur in multiple stages, and we thus used the term "a series" at the top of the definition of functional motions of proteins. In order to simulate such biomolecular functions, we thus have to make use of the multi-scale/multi-physics methods of molecular simulation, including quantum chemistry calculation (QM) and all-atom molecular dynamics simulation (MM), as well as coarse grained model calculation (CG).
Prof. Nir Friedman
DE NOVO ASSEMBLY OF RNASEQ FOR TRANSCRIPTOME RECONSTRUCTION AND CHARACTERIZATION
Defining the complete transcriptome of eukaryotic organisms has traditionally been a challenging task. Advances in sequencing RNA (RNAseq) offer powerful approaches to transcriptomes study. Recently, RNAseq was used to quantify the gene expression levels and identify splice isoforms. However, many studies depend on existing annotation, limiting the ability of discovering novel transcripts, and most require genome sequence, limiting their applicability to organisms without a sequenced genome, complex environmental samples, and cancer.
Here, we present a novel approach for de novo assembly of a transcript catalog from read data alone. We present an algorithm that takes read data and generates a host of assembly graphs, each one ideally corresponding to a single transcript. Our algorithm then extracts from each graph one or more transcript isoforms, quantifies their levels, and scores their confidence. We show how these approaches scale to organisms from yeasts to vertebrates, helping in genome annotation of newly discovered organisms for which complete genome sequence is not available, and for the discovery of novel fusion transcripts in human cancers.
Prof. Hiroki R. Ueda
SYSTEMS BIOLOGY OF BIOLOGICAL TIMINGS.
Mammalian circadian clock system is a complex and dynamic system consisting of complicatedly integrated regulatory loops and displaying the various dynamic behaviors including i) endogenous oscillation with about 24-hour period, ii) entrainment to the external environmental changes (temperature and light cycle), and iii) temperature compensation over the wide range of temperature.
The logic of biological networks such as circadian clocks is difficult to elucidate without (1) comprehensive identification of network structure1-3, (2) prediction and validation based on quantitative measurement and perturbation of network behavior4,6,7, and (3) design and implementation of artificial networks of identified structure and observed dynamics5. In this symposium, I will report on the current progress of the analysis and synthesis of mammalian circadian clocks.
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. Nat Cell Biol. 10, 1154-63 (2008).
. PNAS 106, 9890-5 (2009).
. PNAS 106, 15744-49 (2009).
Prof. David Landsman
Extracting meaningful information from data floods.
Biomedical researchers are facing rapidly increasing volumes of extraordinarily complex data about the composition, structure, and function of genes and their products. An integrated view of the macromolecular components of cells and the interactions that produce biological responses can be addressed using new theoretical and computational methods. New methodologies and protocols for the analysis of these large and complex data sets have enabled biologists to learn substantially more about related sequences from a wide variety of different organisms. Yet, the analysis of biological sequences and structures on a gene-by-gene basis is also still a necessity, as whole genome or chromosome studies usually fail to identify some of the subtle, biologically relevant links that could be discussed but are not because the information exists across several databases. Many biologists remain unaware of information in databases that pertain to their specific interests. A major aim is to unearth useful information that is partially hidden by the sheer quantity of available data, particularly those relating to the complex events in the eukaryotic cell. I will give an overview of where I perceive current research is progressing and where the flood of data is driving new research areas using our own work as examples.