Category Archives: Event

London Perl Workshop 2011

This year’s London Perl Workshop will be held on Saturday 12th November at Westminster University.

It’s free to attend and you can sign up here: http://conferences.yapceurope.org/lpw2011/index.html

The schedule isn’t up yet, but an update sent to the london.pm mailing list promises introductory workshops for programmers of other languages, updates on new Perl developments for current Perl programmers all the way up to advanced talks from world-renowned Perl experts.

VIZBI 2012 – Visualizing Biological Data

VIZBI 2012 – Visualizing Biological Data.

EMBL, Heidleberg 6-8th Mar 2012


SameAs Pub Quiz

The lovely Kaitlin & Matt from SameAs are organising another nerdy pub quiz on Friday 2nd September at 7pm in Juno in Hoxton.

http://sameas.us/events/fringe_quiz

If anyone fancies forming a Biogeeks team, give me a shout.

ISMB/ECCB 2011 – FriendFeed

Microblogging ISMB:

ISMB/ECCB 2011 – FriendFeed.

Science Online London – Communcation – Technology- Eventbrite

Science Online 2011 tickets now on sale:

Science Online London – Communcation – Technology- Eventbrite.

June Tech Meet

KCL Logo

SLaM Logo
 
 
 

This month’s tech meet, organised in association with the KCL Bioinformatics Interest Group (BIG) and the Biomedical Research Centre for Mental Health (BRC-MH), will be at King’s College London, Guy’s Campus (London Bridge) in the Large Committee Room of the Hodgkin Building from 6pm on Thursday 23rd June.

We’ll have some tables booked at The Miller afterwards for more biogeeky chat and beers.

Important!

We only have space for 35 people to participate in the WGCNA talk / workshop, and we expect it to be a popular event, so please email london.biogeeks@gmail.com if you want to be sure of a space.

If you can’t make it to the workshop, feel free to come along to the pub afterwards. We’ll be there from around 7.30.


Steve Horvath

 

Speaker

We’re excited to announce that this month’s meet up will feature Steve Horvath from the Biostatistics Department at UCLA.

Steve is a Professor in Human Genetics and Biostatistics and his group develops biostatistical, computational, and systems biologic methods for studying complex phenotypes. Recent research has focused on the development and application of systems biologic and systems genetic methods for addressing biological, genetic and clinical questions. He’ll be giving us an overview of Weighted Gene Co-Expression Network Analysis (WGCNA).

Bring along a laptop with R and WGCNA installed so you can play along!

 
 


WGCNA

WGCNA

Weighted gene co-expression network analysis (WGCNA) facilitates a systems biologic view of gene expression data. The network framework makes it straightforward to integrate gene expression data with other types of data, e.g. clinical traits and genetic marker data. This talk covers several theoretical topics including network construction, module definition, network based gene screening, and differential network analysis. The methods are illustrated using several applications including i) screening for cancer genes, ii) comparing human and chimp brains, and iii) complex disease gene mapping. Related articles and material can be found at the following webpage http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/


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