IEEE SPS / UBC ICICS Summer School on Signal Processing and Machine Learning for Big Data

PROGRAM

In natural language processing, latent Dirichlet allocation (LDA) is a generative model that allows sets of observations to be explained by unobserved groups that explain why some parts of the data are similar. For example, if observations are words collected into documents, it posits that each document is a mixture of a small number of topics and that each word's creation is attributable to one of the document's topics. LDA is an example of a topic model and was first presented as a graphical model for topic discovery by David Blei, Andrew Ng, and Michael Jordan in 2003.[1]

https://sites.google.com/site/s3pbigdata2014/program

IEEE SPS / UBC ICICS Summer School on Signal Processing and Machine Learning for Big Data

   

	Tuesday July 29	Wednesday July 30	Thursday July 31	Friday August 1
9:00-9:30	Opening ceremony
9:30-10:30	Konstantinos N. Plataniotis University of Toronto	Angshul Majumdar IIIT-Delhi	Ali Bashashti BC Cancer Agency	Ozgur Yilmaz University of British Columbia
10:30-11:00	Coffee break	Coffee break	Coffee break	Coffee break
11:00-12:00	Vikram Krishnamurthy University of British Columbia	Angshul Majumdar IIIT-Delhi	Tom Levi Plenty Of Fish	Michael Friedlander University of British Columbia
12:00-13:00	Lunch	Lunch	Social event with lunch	Rayan Saab University of California, San Diego
13:00-14:00	Georgios Giannakis University of Minnesota	Martin McKeown University of British Columbia
14:00-14:30	Coffee break	Coffee break
14:30-15:30	Georgios Giannakis University of Minnesota	Li Deng Microsoft Research

The Data Effect

http://cityage.tv/thedataeffect/program/


Data has been called our 21st-Century resource. For good reason. We live in a digital age, when data across all sectors of society is being created and stored at historic proportions. How we protect and use that data, as well as structure share and analyze it, stands to transform health care, research and other sectors in Canada.

The Data Effect, now in its fourth edition, has assembled the private, public and research leaders who are capitalizing on data to drive health research and innovation. They are part of the CityAge’s goal to make Canada a leader in the proper and innovative use of data for the public good.

The fourth edition of The Data Effect will build on the inaugural version held in Vancouver in June 2012, which explored how BC’s uniquely high quality population health data can be put to use to save lives and improve health research. Using focused discussions and use cases, the event will address the steps required to make British Columbia a centre for excellence on the use of data for 21st Century advanced health care and research.

APBC 2013

Asia Pacific Bioinformatics Conference
http://www.bioinformatics.ubc.ca/files/2012/01/APBC-2013-Final-Program.pdf

Conference Chair
• Steven Jones, BC Genome Sciences Centre, Canada

Program Chair
• S. Cenk Sahinalp, Simon Fraser University, Canada
Local Organizing Committee
• Inanc Birol, University of British Columbia, Canada
• Cedric Chauve, Simon Fraser University, Canada
• Jack Chen, Simon Fraser University, Canada
• Anne Condon, University of British Columbia, Canada
• Paul Pavlidis, University of British Columbia, Canada
• Sohrab Shah, University of British Columbia, Canada

Steering Committee
• Phoebe Chen (Chair), La Trobe University, Australia
• Sang Yup Lee, KAIST, Korea
• Satoru Miyano, University of Tokyo, Japan
• Mark Ragan, University of Queensland, Australia
• Limsoon Wong, National University of Singapore
• Michael Q Zhang, CHSL, USA and Tsinghua University, China

Program Committee
• Tatsuya Akutsu Kyoto U, Japan
• Rolf Backofen U Freiburg, Germany
• Joel Bader Johns Hopkins U, USA
• Vineet Bafna UCSD, USA
• Niko Beerenwinkel ETH, Switzerland
• Inanc Birol University of British Columbia, Canada
• Mathieu Blanchette McGill U, Canada
• Paul Boutros U Toronto, Canada
• Vladimir Brusic Harvard U, USA
• Cedric Chauve SFU, Canada
• Phoebe Chen LaTrobe U, Australia
• Ting Chen USC, USA
• Jack Chen SFU, Canada

Canadian Society of Microbiologists (CSM)

http://www.csm-scm.org/english/wn_meetings.asp

BC Clinical Genomics Conference

http://bccgn.ca/news-events/Conference.htm

BCCGN holds a conference every spring to facilitate education and research in the area of clinical genomics

BCCGN’s third annual conference, GENOMICS IN MEDICINE 2015 was held on Wednesday April 27th, 2011 at the Vancouver Convention Center. Attending physicians recieved 6 CME credits. It attracted 210 delegates including family physicians and specialists (23%), many of whom (18%) travelled from outside the lower mainland. Also attending were health professionals, researchers and students. Feedback from delegates was very positive for the overall conference program.

Here's some quotes from physicians who attended:-

“I am better prepared for discussion with patients about what genomics can and cannot do for them right now.”

“I learned about the “Fast pace of genomic technology and our lack of preparedness to deal with it.”

ALLEN INSTITUTE FOR BRAIN SCIENCE 2011 Annual Symposium: Open Questions in Neuroscience

http://www.alleninstitute.org/events/symposium/index.html

Sacha B. Nelson, Brandeis University
http://www.bio.brandeis.edu/faculty/nelson.html
Defining the mammalian neurome

Nathaniel Heintz, Investigator, Howard Hughes Medical Institute
http://www.rockefeller.edu/research/faculty/labheads/NathanielHeintz/
Research in Dr. Heintz’s laboratory aims to identify the genes, circuits, cells, macromolecular assemblies and individual molecules that contribute to the function and dysfunction of the mammalian brain. Dr. Heintz and his colleagues have developed a suite of novel approaches based on the manipulation of bacterial artificial chromosomes (BACs) to investigate the histological and functional complexities of the mammalian brain in vivo and to understand how these mechanisms become dysfunctional in disease.

Pamela Sklar, M.D., Ph.D.
http://pngu.mgh.harvard.edu/faculty/sklar/index.php
Genomics and psychiatry

Translational bioinformatics

2011 AMIA Summit on Translational Bioinformatics

http://jointsummits2011.amia.org/TBI/overview

Exponentially growing biological and bioinformatics data sets present a challenge and an opportunity for researchers to contribute to the understanding of the genetic basis of phenotypes. Due to breakthroughs in microarray technology, it is possible to simultaneously monitor the expressions of thousands of genes, and it is imperative that researchers have access to the clinical data to understand the genetics and proteomics

of the diseased tissue. This technology could be a landmark in personalized medicine, which will provide storage for clinical and genetic data in electronic health records (EHRs). In this paper, we explore the computational and ethical challenges that emanate from the intersection of bioinformatics and healthcare informatics research. We describe the current situation of the EHR and its capabilities to store clinical and genetic data and then discuss the Genetic Information Nondiscrimination Act. Finally, we posit that the synergy obtained from the collaborative efforts between the genomics, clinical, and healthcare disciplines has potential to enhance and promote faster and more advanced breakthroughs in healthcare.

http://perspectives.ahima.org/index.php?option=com_content&view=article&id=166:translational-bioinformatics-and-healthcare-informatics-computational-and-ethical-challenges&catid=42:electronic-records&Itemid=88

Cold Spring Harbor (CSH) Asia 2011 Abstracts

http://csh-asia.org/Abstract%20Status/a-system2011_absstat.html

Best Conferences -- GenomeWeb

http://www.genomeweb.com/best-conferences

APBC2012

APBC2012: The Tenth Asia Pacific Bioinformatics Conference, Melbourne Australia

Deadline Approaching: APBC2012 – The Tenth Asia Pacific Bioinformatics Conference

-------------------------------------------------------------------------------------------------------



The Tenth Asia Pacific Bioinformatics Conference

Melbourne, Australia, 17-19 January 2012

http://homepage.cs.latrobe.edu.au/ypchen/APBC2012/



Important Dates

Paper submission: 20th July 2011 *******

Author Notification: 20th Aug 2011

Final Version due on: 1st Oct 2011

Tutorial submission open: 1st July 2011

Poster submission open: 3rd Oct 2011

Registration open: 22nd Aug 2011

Bioinformatics and Integrated Oncology Program Retreat 2011

Ingenuity Pathway
TargetScan
cytopenias - few cells
Comrad - Comrad: a novel algorithmic framework for the integrated analysis of RNA-Seq and WGSS data http://bioinformatics.oxfordjournals.org/content/early/2011/04/09/bioinformatics.btr184.abstract
edge betweeness - edges that occur on many shortest paths between other edges have higher betweenness than those that do not.

triple negative - most aggressive tumour subtype, can't be detected by common markers (ie oestrogen receptor (ER), Her2 - herceptin, progesterone receptor, MUC1, CEA)
  - BRCA1 and BRCA2 are less commonly used because these are found in germ line?

most mutations are found in tp53

http://www.foxnews.com/health/2011/06/02/scientists-testing-new-drug-for-triple-negative-breast-cancer/

The hallmarks of cancer. Hanahan D, Weinberg RA
www.ncbi.nlm.nih.gov/pubmed/10647931


MammaPrint

OncotypeDX

stroma - environment surrounding tumour (can be useful for prediction?)
epithelium - tumor region

PAM50 gene set  - Parker 2009
www.aruplab.com/pam50
Parker JS, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 2009;27(8):1160–7.

Met: Chris Bajdik
http://www.bccrc.ca/dept/cc/chris-bajdik

keynote: Michael Hallett, McGill Centre for Bioinformatics

Bioinformatics conferences

http://www.conference-service.com/conferences/bioinformatics.html

http://kevin-gattaca.blogspot.com/2010/11/2011-bioinformatics-conferences.html

CHI2011 - Computer Human Interface Conference

http://chi2011.org/program/index.html

eps global medical development

http://www.epsglobal.ca/plus/list.php?tid=66

RECOMB 2011

Design of Protein-Protein Interactions with a Novel Ensemble-Based
Scoring Algorithm.
Kyle E. Roberts, Patrick R. Cushing, Prisca Boisguerin, Dean R. Madden
and Bruce R. Donald.
* K*, Protein design, Bruce Donald, Flexible rotamer backbone
* http://ftp.cs.duke.edu/~kroberts/latexProjects/Recomb2011/Final/recomb_calwriteup1.pdf
* http://www.cs.duke.edu/donaldlab/osprey.php
* NSRP - They are synthesized in many bacteria and fungi by large multifunctional proteins called nonribosomal peptide synthetases (NRPS). A unique feature of NRPS system is the ability to synthesize peptides containing proteinogenic as well as non-proteinogenic amino acids. http://linux1.nii.res.in/~zeeshan/nrps.html
* DEE is a provable algorithm, does not produce gaps
* Game theory (minimax) - positive and negative designs

Experiment Specific Expression Patterns.
Tobias Petri, Robert Küffner and Ralf Zimmer.
* Look for genes that deviates from the model 'unexpected genes'
* http://compbio.cs.sfu.ca/recomb2011/recomb2011_submission_249.pdf
* http://www.springerlink.com/content/h725542467jv537j/

NIPS - Neural Information Processing Systems

http://nips.cc/Conferences/2010/Program/schedule.php

http://nips.cc/Conferences/2010/Program/event.php?ID=2291

University of Edinburgh; ; WTCHG Oxford; University of Edinburgh

Poster: Sparse Instrumental Variables (SPIV) for Genome-Wide Studies

Felix Agakov, Paul McKeigue, Jon Krohn, Amos Storkey

M74

This paper describes a probabilistic framework for studying associations between multiple genotypes, biomarkers, and phenotypic traits in the presence of noise and unobserved confounders for large genetic studies. The framework builds on sparse linear methods developed for regression and modified here for inferring causal structures of richer networks with latent variables. The method is motivated by the use of genotypes as ``instruments'' to infer causal associations between phenotypic biomarkers and outcomes, without making the common restrictive assumptions of instrumental variable methods. The method may be used for an effective screening of potentially interesting genotype phenotype and biomarker-phenotype associations in genome-wide studies, which may have important implications for validating biomarkers as possible proxy endpoints for early stage clinical trials. Where the biomarkers are gene transcripts, the method can be used for fine mapping of quantitative trait loci (QTLs) detected in genetic linkage studies. The method is applied for examining effects of gene transcript levels in the liver on plasma HDL cholesterol levels for a sample of sequenced mice from a heterogeneous stock, with $\sim 10^5$ genetic instruments and $\sim 47 \times 10^3$ gene transcripts.