2013-2014 Seminar Schedule

Computational Biology Branch (CBB) is the research branch of the National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institutes of Health (NIH).

We hold weekly seminars by CBB members each Tuesday at 11 AM in the Building 38A B2 NCBI Library. Visitors' presentations usually take place in the same room, but are scheduled on a different day of the week. If scheduling a visitor's presentation, please don't forget to book a seminar room.

To schedule a seminar, please click on the appropriate date in the calendar.

Contact Ivan Ovcharenko with questions or if you need help scheduling a seminar.

Upcoming Seminars

Alexander GoncearencoJanuary 27, 2015 at 11:00
Exploring the interfaces in protein complexes. Predicting protein-protein interactions on a proteome scale by using structural data.
“Virtually all the molecular processes involve protein-protein interactions. In a crowded cell proteins evolved highly specific interfaces in order to recognize the right partners and bind with the desired affinity, which is reflected in their sequence and structural properties. Some interactions are particularly well studied due to their biomedical importance, however the majority of interactions still remain uncharacterized. Structural methods provide invaluable atomistic details of molecular interactions, however the data is scarce. We explore the diversity of interfaces in the PDB and in IBIS, deposition rates and associated coverage of CDD and Pfam families with structural data for protein complexes and suggest new targets for structural genomics. Although high-throughput experimental methods lack accuracy, they allow analyzing protein interactions on a proteome scale. Our goal is to characterize protein interfaces in interactomes structurally and predict novel interactions. We develop a computational protocol for template-based prediction of interfaces. In addition to similarity of binding site residues we account for interface complementarity using statistical potentials. We apply the method to several bacterial and eukaryotic proteomes, discuss the scoring system, validation and benchmarking techniques. Identification of interaction sites with residue-level details on a proteome scale potentially enables a more systematic view on diseases in the context of interaction networks and pathways. Therefore, we develop web tools for interactive analysis of structural interactomes.“

Mario A FloresFebruary 2, 2015 at 11:00
Computational prediction and perturbation analysis of ceRNA networks in cancer
Sajid MarhonFebruary 3, 2015 at 11:00
De novo, DNA Spectral Analysis-Based Technique for Protein-Coding Regions Prediction