VanBUG (Vancouver Bioinformatics Users Group) is an association of researchers, other professionals and students in the B.C. Lower Mainland who have an interest in the field of bioinformatics.

VanBUG meets on the second Thursday of every month from September through April. Research presentations by bioinformatics leaders, students and industry representatives are followed by networking over pizza and refreshments

Meetings are held in the Gordon and Leslie Diamond Family Theatre, BC Cancer Research Centre, 675 West 10th Avenue at 6:00 pm and are free and open to all.

As a service to the community, other bioinformatics events are posted to the Calendar

Visit our sister groups for bioinformatics events in Montreal (MonBUG) and now Toronto (TorBUG)!

next speakers:

Christopher Hogue

Talk Title:

TBA

Date/Time:

Thursday, September 12, 2013, 6:00pm

Affiliation:

Senior Director, Joyent Inc., Vancouver

formerly, Principal Investigator, Research Center of Excellence in Mechanobiology, National University of Singapore

URL:

Christopher Hogue

Abstract:

TBA

Please note:

Trainees are invited to meet with the VanBUG speaker for open discussion of both science and career paths. This takes place 4:30-5:30pm in either the Boardroom or Lunchroom on the ground floor of the BCCRC

Recommended Readings

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Introductory Speaker:

Artem Babaian, Dixie Mager’s lab, Terry Fox Laboratory

Title: 

TBA

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To view previous VanBUG posters and presentations, please see Archives

sponsored by:

 

      

past sponsors:

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Cloud computing has gotten a lot of attention in the last couple of years.  As a result, countless companies (such as Amazon, Rackspace, etc) now offer services for those who need quick access to servers and storage- without the need for server rooms, full time sys admins, etc.

So with all of these pre-existing services for doing cloud computing, why are we creating our own?  There are a few reasons, but one important reason is that scientists often work with BIG data.  When a user needs to upload and/or download hundreds of gigabytes, or even terabytes of data from the cloud, they are limited by the network speeds between their computer and the cloud.  Within the university, we have very good network speeds, which makes it feasible to transfer large datasets to and from servers. What may take hours to transfer to the Amazon Cloud may take minutes to transfer to the Genome Center Cloud.

Service and expertise are another place we hope to add value to the cloud experience.  The Bioinformatics Core has a lot of experience installing and using various scientific software, which we can use to save users hours of frustration when trying to get their research going.  Other services are great, but their only aim is to provide computing resources.  The Bioinformatics Core is here to help you do science!

At the moment, most cloud computing services are aimed at more “run of the mill” users.  Bioinformaticians are a demanding bunch, and when they need a high memory (think 500GB or RAM) or powerful (imagine 50 cores) machine to do an analysis, commercial solutions fall well short (generally they don’t offer more than 70 GB of RAM or 8 cores).

We are currently working on building the necessary infrastructure, and are aiming to make the cloud available to customers by fall 2013.  If you are interested in using the Genome Center Cloud, please email us at ucdbio@gmail.com.

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The core research objectives of Mr. SymBioMath are:

• Research on the Big-Data problems and computational intensive applications in high-performance computing:
• New software libraries for out-of-core management of Big-Data, specially for I/O
• Reduction of the computational space and runtime for all-all sequences
• New data structures for in-core data management to reduce memory demand
  
  
• New data processing applications in comparative genomics, especially those related to Big-Data sets, to allow genome-wide association studies, such as:
• Modelling evolutionary events (SNP, mutations, translocations, deletions, duplications, inversions, etc.) aimed to understand evolution and extrapolate from them the divergence between sequences for phylogenetic tree construction
• Comparison and synthesis of inter-genome distances
• Gene-Gene interactions studies correlated with phenotype data
  
  
• Implementing and packing commercial application prototypes to evaluate the potential for their exploitation in biomedical cases, in concrete in the study of
• Adverse reactions to treatment in allergic patients
• Interfacing, visualisation, and integration of external data sources as well as functional annotations

Agenda:

Tuesday, 10^th of September: Bioinformatics

Time	Presenter	Content
8:30 - 9:00		Registration
9:00 - 9:15	Oswaldo Trelles (UMA, Spain)	Welcome to the summer school
9:15 - 11:15	Alois Regl (JKU Linz, Austria)	- Introduction to bioinformatics - Sequence analysis basics
	Coffee break
11:45 - 13:30	Oswaldo Trelles (UMA, Spain)	Comparative genomics scenarios in Mr. SymBioMath
	Lunch
14:30 - 16:30	Jose Ramon Valverde (Centro National de Biotechnologia, Spain)	Metagenome analysis

Wednesday, 11^th of September: Biomedicine and Systems Biology

Time	Presenter	Content
8:45 - 9:00	James Perkins (SAS, Spain)	Introduction and overview of the day's presentations
9:00 - 9:45	Miguel Blanca, M.D. (Hospital Carlos Haya, Malaga)	Introduction to allergies
9:45 - 10:30	Jose Antonio Cornejo (Hospital Carlos Haya, Malaga)	Using high-troughput studies (e.g. GWAS) to find genes involved in disease and patology
10:30 - 11:15	Ulrich Bodenhofer (JKU Linz, Austria) (TBC)	Overview of GWAS Data analysis
	Coffee break
11:30 - 12:30	Miguel Angel Medina (Biochemistry Dep., UMA, Spain)	An overview of systems biology
12:30 - 13:00	Juan Antonio Ranea (UMA, Spain)	Graphical models of networks and their analysis
	Lunch
14:00 - 14:35	Armando Reyes Palomares (Biochemistry Dep., UMA, Spain)	Tools to investigate the genetic basis of disease
14:35 - 15:10	Aurelio Moya (Biochemistry Dep., UMA, Spain)	Systems pharmacology - using biological networks for drug repositioning
15:10 - 16:30	Patrick Aloy (Institute for Research and Biomedicine, Barcelona, Spain)	Systems biology: Combining wet lab and dry lab experiments
16:30 - 16:50	Marc Streit (ICG, Johannes Kepler University Linz, Austria)	Visualizing bio-molecular data

Thursday, 12^th of September: Cloud computing

Time	Presenter	Content
8:45 - 9:00	Michael Krieger (RISC Software, Austria)	Introduction and overview of the day's presentations
9:00 - 10:00	Paul Heinzlreiter (RISC Software, Austria)	Overview on Cloud Computing
10:00 - 11:00	Michael Krieger (RISC Software, Austria)	Hadoop, HBase, And MapReduce (Theory)
	Coffee break
11:30 - 13:00	Paul Heinzlreiter (RISC Software, Austria)	Cloud Computing (Practice)
	Lunch
14:00 - 16:30	Michael Krieger (RISC Software, Austria)	Hadoop, HBase, and MapReduce practice

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Source:kenresearch

The report titled “India Bioinformatics Industry Outlook to FY’2018 - Surging Government Initiatives to Foster Future Prospects” provides a comprehensive analysis of the market size of the India bioinformatics industry by revenue from domestic sales and exports, market segmentation of bioinformatics by application in different sectors such as agriculture biotechnology, medical biotechnology, animal biotechnology, environmental biotechnology, forensic biotechnology and others, by products and services such as bioinformatics knowledge management tools, bioinformatics services and bioinformatics platforms and by various applications such as genomics and transcriptomics, proteomics and metabolomics, pharmacogenomics, molecular phylogenetics and drug design. The report also entails the market share of major bioinformatics companies in India by revenue along with the company profiles of major bioinformatics and genomics companies. An analysis of the future of India bioinformatics industry is provided on the basis of revenue of the market over next five years.

The bioinformatics sector in India has faced many challenges over the years; however this industry has managed to sustain itself and has showcased healthy growth.

The industry has grown at a CAGR of 12.3% over the period FY’2007-FY’2013 and reached INR ~ million in FY’2013. The rising trend in the growth rate of domestic revenue in the bioinformatics market in India has paced since FY’2010. In FY’2012, the domestic bioinformatics market generated revenue of INR ~ crores which constituted ~ % of the revenue of the bioinformatics market in India. During FY’2010-FY’2013, the revenue created by exports was on an average ~ % of the entire bioinformatics revenue in India. Public funding towards research and development (R&D) from the Government of India, decline in costs of human genome sequencing, increase in R&D investments by companies and increase in the number of orders for contract research activities are leading to the increase in bioinformatics revenue in India.

The use of bioinformatics in the agriculture biotechnology sector has grown at a CAGR of 13.9% over the period FY’2007-FY’2013. The contribution of medical biotechnology to the overall bioinformatics market in India has witnessed an increase from ~% in FY’2007 to ~% in FY’2013. In FY’2013, animal biotechnology contributed nearly ~% in the bioinformatics revenue whereas the contribution of environmental biotechnology was recorded as ~% during the year. Forensic biotechnology has grown at a CAGR of 6.1% during the period FY’2007-FY’2013 while marine biotechnology and academics generated revenue of INR ~ crores in FY’2013.

The products and services segment of the bioinformatics industry in India has been majorly driven by the bioinformatics services. The bioinformatics services have grown at a CAGR of 14.2% during FY’2007-FY’2013 and reached a revenue figure of INR ~ crores in FY’2013. The bioinformatics knowledge management tools generated a major part of the revenue from the sequence analysis tools over the years. In FY’2013, the revenue from the tools segment was INR ~ crores. Bioinformatics platforms generated revenue of INR ~ crores in FY’2013 which is considerably higher as compared to the revenue generation of INR ~ crores in FY’2007.

In FY’2013, genomics and transcriptomics held nearly ~ % of the overall bioinformatics market revenue in India followed by proteomics and metabolomics which accounted for ~ % of the overall revenue of the bioinformatics market in the country in FY’2013. The revenue generated through application of pharmacogenomics in bioinformatics market in the country was INR ~ cores. Pharmacogenomics segment grew at a CAGR of 12.4% during the period FY’2007-FY’2013. Molecular phylogenetics forms ~ % of the total bioinformatics revenue in FY’2013 while ~ % of the revenue was generated through the field of drug design for the overall bioinformatics sector in India.

The bioinformatics market in India is highly fragmented with a large number of mid-sized and small players. A few large players contribute a major part of the revenue of the industry. The bioinformatics market in India is largely held by Strand Life Sciences, Ocimum Biosolutions and Molecular Connections which captured nearly ~% of the market in FY’2013. Strand Life Sciences is the largest player in bioinformatics market in India, capturing a market share of ~ % in FY’2013. Companies from the information technology (IT) sector are also gradually gaining a foothold in the bioinformatics industry in the country, by developing innovative products and services.

The ongoing trends in the bioinformatics industry in India have showcased that genomics, translational bioinformatics and personalized medicine will be the major driving segments of the industry over the next few years.

Key Topics Covered in the Report:

1. The market size of the Indian Bioinformatics Industry , FY’2007-FY’2013
2. Market segmentation of India bioinformatics industry by application by sectors, FY’2007-FY’2013
3. Market Segmentation of India bioinformatics industry by products and services,FY’2007-FY’2013
4. Market Segmentation of India bioinformatics industry by applications of bioinformatics ,FY’2007-FY’2013
5. India bioinformatics industry trends and developments
6. Government regulations and initiatives of India bioinformatics industry
7. Major bioinformatics research institutes in India
8. Market Share of leading players in bioinformatics industry in India,FY’2013
9. Company profiles of major players in India bioinformatics industry
10. Future outlook and projections on the basis of revenue in India bioinformatics market, FY’2014-FY’2018

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SLEA is a method to analyse the transcriptional status of gene modules (gene sets) per sample in a transcriptomic dataset. The results are presented in the form of interactive heatmaps which facilitates their interpretation. It can be used to identify tumor subtypes, correlate molecular features with clinical features and study relationship between modules.

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Tasks

1. Integration and analysis of large amounts of data from genomics, transcriptomics and metabolomics experiments
2. Support the development process for the production of various bio-based products through comparative analyzes of microbial production strains and target identification to increase productivity
3. Processing of biotechnological issues by statistically significant responses from omics experiments
4. Support of existing software platforms and databases
5. Creation and capture of requirement profiles for new IT projects, evaluation of alternative solutions, as well as coordinating the development and implementation of new software systems

For more information about our Health & Nutrition Business you like to visit our website .

Conditions:

1. University degree in computer science
2. Designated trademarks and skills in the areas of bioinformatics: integration, visualization and analysis of omics data (genome, transcriptome, metabolome)
3. High team spirit and care and personal initiative, reliability and flexibility
4. Good German and English, spoken and written

What we offer

They work together with a team of exciting and challenging topics in a highly modern, innovative and creative environment. Intensive training "on the job" with competent colleagues guarantees a quick introduction to the self-responsible task processing. Performance-related pay, the promotion of your personal development and professional qualifications are of course for us.

Your application

Have we piqued your interest?

Then apply online via our career page at www.evonik.de / careers .

Your questions, please contact Dr. Julia Tolsdorf, TELEPHONE +49 800 2 386,645th 

CODE POINT OF EU - 5805

Author:Posted by Erika Check Hayden

Bioinformaticians today published a mammoth evaluation of genome assemblers — computer programs that aim to piece together short DNA sequence reads into complete genomes.

Their work, described in the journal GigaScience, was conducted for the second Assemblathon, a contest designed to compare and evaluate competing genome assemblers. In the current round of the contest, which started in July 2011, 21 teams submitted 43 attempts to assemble three genomes from scratch: that of a bird (budgerigar), a fish (the Lake Malawi cichlid) and a snake (the boa constrictor).

One notable finding from the contest was that different assemblers — and the same assemblers in the hands of different teams — did not give consistent results. That echoes the results of Assemblathon 1, which wrapped up in 2011. But the problem itself may be more significant now than it was then, owing to the democratization of genomics, with many more labs now using many more methods to assemble many more genomes from scratch.

Perhaps because of this, Assemblathon 2 has sparked a bit of soul-searching among bioinformaticians, who have debated its results and their significance since a preprint of the paper was posted on arXiv in January. 

Bioinformatician C. Titus Brown of Michigan State University in East Lansing, who reviewed the paper,published his review and wrote on his blog in February: “the biggest outcome of the Assemblathon 2 paper can be stated quite simply: we’re doing it all wrong, in bioinformatics…as a field, we have pretended that genome assembly is a reliable exercise and that the results can be trusted; the Assemblathon 2 paper shows that that’s wrong.”

Keith Bradnam of the University of California in Davis, the paper’s first author, doesn’t fundamentally disagree with that take: “I agree that the science community should be better at explaining that genomes and genome assemblies are the results of individual experiments that are rarely ever replicated. Trust them at your peril,”he commented on Brown’s post.

This isn’t an ideal situation for the average scientist who just wants to know which is the best tool to use for a specific project. On the blog Haldane’s Sieve, Bradnam compares the process of selecting an assembly method to that of choosing the best pizzeria in Davis.

“[T]he notion of a ‘best’ pizza is highly subjective and the best pizza for one person is almost certainly not going to be the best pizza for someone else,” Bradnam writes.

“Just as it might be hard to find somewhere that sells an inexpensive gluten-free, vegan pizza that’s made with fresh ingredients, has lots of toppings and can be quickly delivered to you at 4:00 am, it may be equally hard to find a genome assembler that ticks all of the boxes that you are interested in.”

See links to all the commentary on today’s paper at the Assemblathon web page.

Follow Erika on Twitter @Erika_Check.

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