Tag Archives: seminar

Imperial College Centre for Integrative Systems Biology and Bioinformatics Seminar Series

All are welcome to the following CISBIO seminars – venues as listed:


Monday Feb 13th, 4.30pm
7th Floor common room
Sir Ernst Chain Building – Wolfson Laboratories (formerly Biochemistry)

Dr Guido Sanguinetti,
University of Edinburgh

Latent switching models of transcriptional regulation

Abstract: I will review the use of a class of continuous-time models of transcriptional regulation. This consist of a system of (ordinary or stochastic) differential equations whose coefficients depend on a latent, discrete state Markov Jump process. The interpretation we will propose is that the DEs describe the dynamics of expression of a set of genes, while the latent processes describe activation states of transcription factor proteins. I will describe the approach to inference, and present results on a number of real data sets.

http://homepages.inf.ed.ac.uk/gsanguin/research.html


Monday 5th March, 4 pm
G34 Lecture Theatre, SAF (Sir Alexander Fleming) building

Dr Nick Le Novère
EMBL – European Bioinformatics Institute

This or that – Allosteric Calcium Sensors and Synaptic Plasticity

http://www.ebi.ac.uk/~lenov/


Monday 12th March, 4pm
G34 Lecture Theatre, SAF (Sir Alexander Fleming) building

Dr Mario Caccamo
The Genome Analysis Centre (TGAC)

Computational analysis of next generation sequencing (provisional title)

http://www.tgac.ac.uk/bioinformatics/


Monday 26th March, 4.30pm
Rm 122, SAF (Sir Alexander Fleming) building

Prof Jürg Bähler,
University College London

Quantitative Analysis of Fission Yeast Transcriptomes and Proteomes

www.bahlerlab.info

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Joint UCL Computational Biology / CoMPLEX Seminar

3D Protein Structure Predicted from Evolutionary Sequence Variation

Chris Sander, Debora S. Marks

3pm 1st July 2011, University College London

http://www.ucl.ac.uk/computational-biology/

Abstract

The trajectory of an evolving protein through sequence space is constrained by the need to maintain structure and function. Residues in spatial proximity tend to co-evolve, yet attempts at inverting the evolutionary record to derive proximity constraints have so far been inadequate. Here we use constraints inferred from evolution to predict de novo3D protein structures, without use of homology modeling or fragments from known structures. Our evolutionary constraints tackle the major obstacle in state-of-the-art de novo prediction: the ability to sample 3D conformational space. The predicted constraints are calculated with a method borrowed from statistical physics using maximum entropy which solves the inverse problem of inferring spatial proximity from patterns of co-evolution. We report prediction for 12 proteins ranging from 20-220 residues in size at a Ca-RSMD of 2.8 – 5.1 Å. The predicted structures have excellent topological agreement with experimentally determined structures, with structural elements well placed in 3D space, suggesting they can be refined further. In this era of massive genomic sequencing across many species, the evolutionary record captured in sequence alignments provides an increasingly powerful source of predictive information, in particular for protein families that have resisted experimental structure determination.

Venue

Medawar Lankester Lecture Theatre – behind Foster Court

UCL Cruciform Building