לוח שנה משולב

The performance of self-assembled systems in functional organic materials with electronic or bioactive properties critically depends on the organization and dynamics of the molecular building blocks. Understanding the self-assembly pathways involved in the formation of these supramolecular materials is essential. Although studies under thermodynamic and kinetic control have been performed, quantitative insight into the self-assembly pathways of these structures is lacking. Recent studies on the growth of protein fibrils introduced the concept of pathway complexity extending the traditional concepts of homogeneous and secondary nucleation events in single pathway assemblies. We will discuss crucial steps in the quantitative understanding of pathway complexity in synthetic homogeneous supramolecular polymerizations using chirality as an experimental tool. By obtaining these kinetic parameters, it is now possible to disclose hidden pathways during supramolecular polymerization processes. In the presentation, we show that the chemical self-assembly of chiral π-conjugated oligomers, operates via a nucleation – elongation pathway and hence is highly cooperative. As a result the solvent plays an essential role in the chemical self-assembly and strong evidence is found that the alkane solvents are co-organized with the oligomeric stack. These results are also of crucial importance for the discussion whether the chemical self-assembly creates the thermodynamically determined product or that is possible to form kinetically trapped structures as well. With this knowledge we will show some new functional supramolecular materials.

The MIT BioMicro Center is an integrated genomics facility that provides both expertise and equipment for systems biology. We offer researchers comprehensive genomics services, from experimental design to data analysis. Samples represent broad basic and translational research projects done at MIT. During the talk, I will discuss the challenges we face applying next generation sequencing techniques to research at MIT and how we overcome them.

We present GeneAnalytics, a novel and simple to use gene-set analysis website, and VarElect, a phenotype interpretation tool which provides phenotype-dependent variant prioritization. GeneAnalytics was developed for biological researchers, allowing them to get an impression of the underlying biological processes occurring in their input gene-sets, e.g. a list of differentially expressed genes. GeneAnalytics searches for shared function and expression, without the need for a bioinformatician. Its expression-based analysis is powered by LifeMap Discovery®, which associates between genes and specific tissues, cells and diseases through a sophisticated analysis of manually curated and proprietary gene expression data of normal and diseased tissues and cells. Function-based analysis is based on shared diseases, pathways, Gene Ontology terms, and compounds. VarElect prioritizes a gene list in relation to phenotype/disease related keywords, via disease association, gene function, publications and various other data. VarElect also finds indirect associations, such as through shared pathways or interacting proteins. Both GeneAnalytics and VarElect leverage: GeneCards® – the human gene database, MalaCards – the human diseases database, PathCards- the biological pathways database and LifeMap Discovery® – the embryonic development and stem cells database.
This seminar will describe both systems, as well as highlight case studies from the Department of Molecular Genetics that were elucidated by their insights.