• source of this article:   

    • Published by:Nicky Phillips(Nicky Phillips is a Science Reporter for The Sydney Morning Herald.)
  • Emeritus Professor Terry Speed has been awarded the 2013 Prime Minister's Prize for Science for his contribution to making sense of genomics and related technologies.
  • Their research topics couldn't be more distinct - one study's plants; the other, particles - but a pair of Sydney scientists now have something in common, they are recipients of two of the country's most prestigious science awards, the Prime Minister's Prizes for Science.
  • Engineer Andrea Morello, an associate professor at UNSW, was honoured for his groundbreaking work on quantum computers while evolutionary ecologist Angela Moles was awarded for her research on global patterns in plant life.
  • Dr Moles, also an associate professor at the University of NSW, said she was shocked to receive the $50,000 Frank Fenner Prize for Life Scientist of the Year.

Mathemetician Terry Speed in his office at the Walter and Eliza Hall Institute of Medical Research.

Mathemetician Terry Speed in his office at the Walter and Eliza Hall Institute of Medical Research. Photo: Penny Stephens

"The person who won the award I'm getting last year grew fully functioning breasts from stem cells, that is way cooler than what I do," she said.

  • The overall winner of the $300,000 Prime Minister's Prize was Melbourne statistician Terry Speed, whose mathematical expertise has been used in several high-profile court cases.
  • At the 1994 murder trial of American football player OJ Simpson, Professor Speed, now the head of bioinformatics at the Walter and Eliza Hall Institute for Medical Research, was an expert witness on DNA forensics for the defence. This involved calculating the odds of a chance DNA match, verses a real match of two blood samples.

Associate Professor Angela Moles, UNSW Faculty of Science, and Associate Professor Andrea Morello, UNSW Faculty of Engineering, on the UNSW campus.

Honoured: Associate Professor Angela Moles (left) and Associate Professor Andrea Morello on the UNSW campus. Photo: UNSW/Peter Morris

However Professor Speed, 70, describes his bit-part on the criminology stage as "just a sideshow" in his scientific life which has included two decades at the University of California, Berkeley, the University of Sheffield, the University of Western Australia and CSIRO, where he was the head of statistics and mathematics division.

  • Professor Speed was present his award by Tony Abbott at a ceremony at Parliament House on Wednesday evening.
  • As part of the World Herbivory Project, Dr Moles she spent two years travelling to 75 ecosystems, visiting every continent bar Antarctica, to record the seed size of nearly 13,000 plants and the heights of 22,000 plants.
  • Her findings overturned several long-held ideas of ecology, including the notion that because the tropics contains the most species diversity, plants there would contain the most biologically active compounds - a source of potential new drugs.
  • Instead Dr Moles found plants closer to the poles, which have to tolerate harsher, more variable environments, had a greater variety of chemical defences.
  • More recently her work has shown introduced plants are quickly becoming more versatile invaders which have evolved to suit Australia's climate.
  • Across campus, Dr Morello - winner of the Malcolm McIntosh Prize for Physical Scientist of the Year - and his team have made significant progress in global race to build super-powerful computers.
  • They use the bizarre properties of subatomic particles to perform calculations trillions of times faster than conventional computers.
  • In 2012 the team built the world's first quantum bit, the basic data unit in quantum computers, and the equivalent of 1s and 0s in conventional computers, based on a single phosphorus atom implanted in a silicon chip.
  • A year later they built even smaller, developing a quantum bit, or qubit, based on the core of a phosphorus atom, its nucleus.
  • Australia leads the world in research on quantum computing, with scientists, including Dr Morello's group, achieving several breakthroughs in the past five years.


Published by:Nicky Phillips(Nicky Phillips is a Science Reporter for The Sydney Morning Herald.)




UK Minister for Universities and Science David Willetts joined key stakeholders in the Cambridge biotechnology cluster today to celebrate the opening of a new Technical Hub for bioinformatics.

  • The European Bioinformatics Institute's new South Building will be home to the ELIXIR Directorate, which will coordinate bioinformatics activities throughout Europe in order to increase the availability and uptake of biological data in commercial and non-commercial R&D.
  • As bioinformatics involves analysing very large volumes of data about living things, it is essential for tackling the serious challenges our society faces, from providing healthcare to an ageing population to securing our food and water resources. The new facilities will enable researchers throughout Europe to remain competitive in this expanding area, and will secure the UK's position at the forefront of bioinformatics.

Science and Universities Minister David Willetts said: "This new facility is the embodiment of our investment in big data and bioinformatics. We are not only ensuring that people will receive better services and resource security, we are also maintaining UK leadership in the global science race."

  • The South Building has been funded through a Large Facilities Capital Fund grant via the UK Research Councils, led by the Biotechnology and Biological Sciences Research Council (BBSRC). This financing also supports technical infrastructure and equipment, which enables EMBL-EBI to increase its capacity in data handling and storage.

Professor Jackie Hunter, BBSRC Chief Executive, said: "Investing in this infrastructure ensures that we can create opportunities from the vast quantities of biological data that today's research generates. These state-of-the art facilities will assist our research community in finding solutions to society's challenges faster than ever before."

  • EMBL-EBI delivers world-leading, freely available data on genes and other molecules to researchers in industry and academia. The new building will house EMBL-EBI staff; an Industry and Translation suite, offering space for collaboration with industry partners in the spheres of pharma, agribusiness, biotech and consumer goods; and the Directorate and technical staff of the ELIXIR Technical Hub. ELIXIR is a pan-European infrastructure for the sharing of biological data, funded through sustainable contributions from national member states and the European Commission.




Professor Voronov

    Job Description

    - Ideal Computational Skills (doesn’t have to be all of them):   Matlab, Fortran, Image Processing, Machine Learning (Neural Networks, Bioinformatics), Fluid Dynamics (Lattice Boltzmann Method), Parallel Programming(MPI/OpenMP), Supercomputing, Linux

    - Educational Background:  MS in Chemical Engineering or related field is highly desired (although, if your skills are right, diplomas from other fields will be considered and you will have to take some additional courses to transition to ChE; same for BS).

 Possible Projects (most likely the first two):


  • Developing a Model for Thrombus Formation Based on In-Vivo Confocal Microscopy Images

  • Simulation of Artificial Bone Tissue Growth in Porous Scaffolds in a Flow Perfusion Bioreactor

  • Designing Superhydrophobic Surfaces for Maximum Contact Angle and Friction Drag Reduction

  • Porous Media Flows for Enchanced Oil Recovery


Staring Date:  Spring 2014 semester (application deadlines are NOW, so you should have your letters of recommendation, GRE and TOEFL /or equivalents/ in order)


To Apply:




Job Description:

  • Dr. Curtis Huttenhower in the Biostatistics Department of the Harvard School of Public Health seeks a postdoctoral fellow.
  • The successful candidate will be responsible for funded research projects including methods development for high-dimensional multivariate phenotype association and applications to metagenomic biomarker discovery.
  • The Huttenhower lab is broadly engaged in multiple collaborative studies of the roles of the human microbiome in health and disease, with a focus on computational methods to characterize biomolecular functions within these microbial communities and their interactions with host immunity and genetics.

The postdoctoral fellow will perform:

  • quantitative methods development for the analysis of structured high-dimensional phenotypic, genetic, genomic, and metagenomic data. Specifically, computational methods are required to control false discovery rates when integrating multiple genetic (e.g., polymorphisms), genomic (e.g., gene expression), metagenomic, and phenotypic (e.g., disease status, biometrics, demographics, diet) data types.These methods will in turn be applied to the integration of multiple studies of the structure and function of the human microbiome in order to determine its causal and correlative associations with disease phenotypes.
  • The candidate will be responsible for both computational methods development and these initial applications, should be broadly conversant with bioinformatic techniques for genomic data analysis, and will be supported by programming staff for the implementation of developed methods as publicly available research software.

The position will be located within the Department of Biostatistics at the Harvard School of Public Health; the Huttenhower group works closely with the Broad Institute, the Human Microbiome Project, the Dana-Farber Cancer Institute, and the broader Boston biomedical and life sciences communities, resulting in a rich environment for quantitative, computational, and laboratory collaborations.


Doctoral degree in Computer Science, Bioinformatics, Biostatistics, Biology, or a related field; familiarity with functional genetic and/or genomic data, as indicated by publication record; proficiency in one or more statistical or scripting languages appropriate for scalable data analysis; ability to communicate scientific material and collaborate well.

To Apply

Please submit a cover letter (including a brief but detailed statement of interest), CV, and contact information for at least three references to Dr. Curtis Huttenhower at [email protected] AND to [email protected].

New VCU logo

Job Description

VCU’s Center for Biomarker Research and Personalized Medicine ( seeking a post-doctoral researcher to help analyze data from a large methylation project of Major Depressive Disorder (MDD).

The goal is to find methylation markers that predict chronic MDD. For this purpose we will sequence over 1,600 methylomes in whole blood as well as post-mortem brain samples.


    • Candidates should have formal training in statistics/bioinformatics along with practical experience in analyzing large scale data sets and an interest in MDD.
    • S/he will employ approaches to analyze the datasets that are generated in-house using next-generation sequencing. Experience with Linux/Unix and scripting languages such as R or PERL is important.

The project is highly multidisciplinary and interactive involving other center members plus external collaborators in the US and abroad. The Center is well funded and equipped, occupying a suite of state-of-the-art laboratories. The position is initially for two years and offers ample opportunities for publishing articles and career development.

To Apply

All interested applicants should email a current resume to: Gioia Casso [email protected]


Job Description

  • PhD positions in data mining/machine learning/information systems are available in the Center on Stochastic Modeling, Optimization, & Statistics (COSMOS- and the department of Industrial & Manufacturing Systems Engineering (IMSE) at University of Texas at Arlington (
  • Accepted Ph.D. students will be provided with full financial support for the entire PhD study (mostly 4 years for master graduates and 5 years for bachelor graduates). 


  • Graduate or undergraduate students with background in data mining, machine learning, mathematical modeling/optimization, bioinformatics/biomedical engineering, computer science, systems & control engineering, information systems, statistics  electrical engineering are encouraged to apply.

If you are interested, please send your CV, transcripts, and TOEFL/GRE scores (if available) to Dr. Wang at [email protected]. Especially for those who hope to start in spring 2014 are still encouraged apply and send your CV to Dr. Wang as soon as possible (His professional website is: We will make a quick offer decision for Spring 2014. Offers for fall 2014 will be also given to qualified applicants on a rolling basis. 

Current Research Projects:

  • Intelligent Data-Driven Decision-Making Systems
  • Computational Models for Medical/Biomedical Decision-Making
  • Preventive and Personalized Healthcare
  • Biomedical Data Mining & Knowledge Discovery/Bioinformatics
  • Process Monitoring, Surveillance & Warning Systems
  • Functional and Diagnostic Brain Imaging Analysis/Brain Mapping Research
  • Intelligent healthcare control systems/Personal-care Robotics

How To  Apply

    • Those who are interested can send your CV, transcripts and TOEFL/GRE score(if available) to Dr. Wang by [email protected].  We will pre-review the PhD applications quickly on a rolling basis.
  • If you are considered for full financial support or have high chance to get the Engineering College Fellowship, we will recommend you to go to finish the official online application for the graduate school of University of Texas at Arlington.
  • All applicants are required to complete the: GRE General Examination and  TOEFL (for non-native English speakers). A formal application for graduate study at the UT Arlington can be completed online at:

About this course :

This course explains one of the key molecules in life: Deoxyribonucleic Acid (DNA). DNA stores the genetic information in all living cells. The sequence of its building blocks defines both individual identity and species diversity. Changes in DNA can lead to cancer and other diseases. DNA-based technology is now used to detect and treat diseases.

Course Structure

The course will be organized into 14 units of approx. 15 min each. The units will follow a common scheme with a short introductory sequence that discusses the importance of the topic covered. The main part of the lecture will have molecular models, power point animations, live drawings, and short lecture video sequences. At the end of each unit, we will provide a question catalogue and links to supporting material. Immediate self testing will be possible through multiple choice questions and interactive tasks. As homework, students will work on "open questions" in student-centered discussion groups. Open questions are based on but not restricted to the material covered in the course, and students will be encouraged to do their own reading to answer them.
The fourteen units comprise the following topics:
  • 1. How DNA is present in everyday life (DNA History I)
  • 2. DNA History II
  • 3. The structure and properties of DNA – DNA fingerprint
  • 4. Replication – the copying of DNA
  • 5. From DNA to Protein I - Transcription of Genes
  • 6. From DNA to Protein II - RNA processing
  • 7. From DNA to Protein III – translating the genetic code
  • 8. Methods I – making Genes visible
  • 9. Methods II – amplifying Genes
  • 10. Introduction to Genetic Diseases - Cancer
  • 11. Consequences of Mutations
  • 12. How to repair mutations?
  • 13. Muscular Dystrophies - when muscles die
  • 14. Stem Cell Therapies – replacing defective cells
Learning Outcomes
Participants will be able to answer the following questions after completing the course:
  • 1. Why and how has DNA become one of the most powerful tools in research?
  • 2. What exactly does gene therapy mean?
  • 3. Why is it so hard to find a cure for cancer?
  • 4. For which diseases may DNA-based technology help developing a therapy?
  • 5. What are potentials and risks in gene-based medicine?
Prior Knowledge
Participants that possess an interest in modern biomedical research will be able to grasp the key concepts without strong background knowledge. In order to pass the final exam, though, high school level knowledge in chemistry and biology will be advantageous when we draw chemical structures or address cell biological questions.

Course instructors


Dr. rer. nat. habil. Susanne Illenberger
University Lecturer of Biochemistry and Cell Biology, Jacobs University Bremen
Susanne Illenberger has been teaching biochemistry and cell biology at the School of Engineering and Science at Jacobs University Bremen since 2007. She completed her studies of biology at the University of Hannover, Germany in 1992. From 1993-1996, she continued as a PhD in biology in Hamburg, followed by an occupation as a postdoctoral fellow at the Max-Planck-Unit for Structural Molecular Biology at DESY, Hamburg. Between 1998 and 2003, she worked as a scientific assistant at Technical University of Braunschweig, where she received her habilitation and a teaching permission in cell biology and was a private lecturer until 2007.
Go to Profile

Dr. rer. nat. habil. Susanne Illenberger

Prof. DPhil. Sebastian Springer
Associate Professor of Biochemistry and Cell Biology, Jacobs University Bremen
Sebastian Springer’s experimental work is dedicated to the molecular mechanism of antiviral immune response in mammals. In particular, he focuses on the intracellular transport of membrane proteins. He started studying biochemistry in Tübingen in 1985 and graduated with a diploma in 1992. Between 1996 and 2001, he worked as a postdoctoral fellow at the University of California, Berkeley. In 2001, Springer became associate professor of biochemistry and cell biology at Jacobs University Bremen.
Find more information about Prof. Springer’s research and publications on:


Shankar Subramaniam (left), a bioengineering professor at the UC San Diego Jacobs School of Engineering in a meeting with members of his lab, which focuses on bioinformatics, systems biology and systems medicine. He is the corresponding author on the Nature Scientific Reports  paper.

Source of this article:

( —Bioengineers from the University of California, San Diego have created a new method for analyzing RNA transcripts from samples of 50 to 100 cells. The approach could be used to develop inexpensive and rapid methods for diagnosing cancers at early stages, as well as better tools for forensics, drug discovery and developmental biology.

The protocols, which were published in April 2013 in the journal Nature Scientific Reports, are now being applied to a wide range of biological and medical research questions from brain cancer, to liver function and stem cell biology.

The approach from the UC San Diego bioengineers is called Designed Primer-based RNA sequencing or "DP-seq." It's a new tool for generating comprehensive snapshots of RNA—the "transcriptome"—collected from as little as 50 picograms of RNA. Analysis of the transcriptome provides insights into what biological processes are occurring at a specific moment in time. RNA transcripts serve as a proxy for which genes are being expressed and at what levels.

"In the months since we published the DP-seq protocol, there has been tremendous interest from the scientific community," said Shankar Subramaniam a bioengineering professor at the UC San Diego Jacobs School of Engineering and the corresponding author on the paper. "When you are not restricted to samples of thousands of cells, there are so many more system-wide gene expression questions you can ask, and answer," said Subramaniam. Questions like: What transcription factors will determine cell fates, such as cancer versus normal? and what pathways are likely to be activated in a tissue upon treatment with a drug?

Targeted Amplification

Despite the small amounts of RNA inputs required, the DP-seq protocol preserves the relative abundance of RNA transcripts, even for low and moderately expressed transcripts.

In addition, DP-seq can be used to target amplification of specific, medium or lower abundance RNA transcripts by reducing amplification of highly abundant RNA transcripts. With targeted amplification, researchers can gain insights on the low and moderate frequency RNA transcripts that can get lost in the amplification process in other protocols.

"One of the exciting things about our protocol is that it has the potential to perform targeted amplification of genes of interest and/or specific regions of the transcriptome which carry disease-causing mutations or SNPs. Selective amplification of these transcripts will allow massive multiplexing of the samples, opening the door to cost-effective diagnostics," said Vipul Bhargava, a graduate student in the Subramaniam laboratory and the first author on the paper in Nature Scientific Reports. In August 2013, Bhargava completed his Ph.D. in bioengineering at UC San Diego.


To demonstrate this selective amplification, the researchers designed primers that suppressed amplification of highly expressing ribosomal transcripts in embryonic stem cells of mice. This, along with high sensitivity and the large dynamic range offered by DP-seq, uncovered RNA transcripts that had previously only been detected in later stages of embryonic development known as germ layer segregation.

"The majority of the novel transcripts that we identified in our study were low expressed. The high sensitivity in quantification of those transcripts and the large dynamic range offered by our protocol—over five orders of magnitude in RNA concentration—allowed us to detect the expression of these transcripts," said Bhargava.

The DP-seq protocol is one of several approaches developed over the last two years capable of generating transcriptomes from approximately 50 picograms of RNA. The new protocols from UC San Diego, however, offer distinct advantages, the researchers say. For example, by using 44 heptamer primers for cDNA amplification, the DP-seq approach generates transcriptomes faster and more economically than approaches that rely on full-length cDNA amplification of extremely small RNA samples.

The researchers hope to develop their technology for routine diagnosis of pathologies as well as for discovery of mechanisms and targets for therapeutic interventions.

Towards Systems Health

DP-seq is a next-generation sequencing-based approach to whole transcriptome analysis. At its base is one of the central dogmas of biology: DNA is transcribed to form RNA which is then translated to generate proteins—which may be modified before the proteins carry out their prescribed tasks.

Analyzing which RNA transcripts are present, and at what levels—transcriptome analysis—provides a snapshot of system-wide gene expression patterns and a state of the system.

"If you want to address a particular disease, the days of just looking into one gene, one protein or one signaling pathway are over. You need to look at all levels of complexity, all the way from genomic DNA to RNA to proteins, as well as how different modifications happen at the RNA and protein levels," said Bhargava.

Approaches like DP-seq, which provide quantitative data on gene expression levels system-wide, are part of a shift toward "systems health" in which researchers build systems-level models that describe biological phenomena and explain what causes disease.

Once you identify genes that are changing their expression patterns, you can investigate how these genes are interacting with each other and build networks. Through these network models, you can begin to understand how specific changes within one network can affect the overall system. Understanding how perturbations in a system cause disease can lead to new therapies.

A patent has been filed for this technology, which is available for licensing.

Systems Biology at UC San Diego

"I am excited to see all the recent activity in the area of systems health. So much of it is built upon systems biology, and researchers from all across UC San Diego played key roles in creating systems biology," said Subramaniam.

Traditionally, in biology, researchers looked at individual parts—molecules, tissues, physical measures such as cholesterol, or individual physiology readouts like systolic and diastolic pressures. This is analogous to looking at parts of an automobile rather than looking at the automobile as one functioning entity.

In contrast, engineers are trained to look at how components integrate to give systems-level properties. Researchers at UC San Diego were some of the first to bring rigorous principles of engineering and systems-level thinking to the study of biology and medicine.

Subramaniam, for example, was highly involved in a large-scale collaborative grant from the NIH National Institute of General Medical Sciences (NIGMS) that focused on cell signaling. This was the first systems biology project to focus on mammalian systems, and it brought together UC San Diego researchers from engineering, medicine, life sciences and the San Diego Supercomputer Center.

"Bringing engineering principles into systems biology was done first by researchers here at UC San Diego," said Subramaniam. "Modeling biological systems as well as disease based on their parts, and making the models context specific, that was new."

The early research raised questions that led the researchers to ask—and find ways to answer—questions from a systems-level perspective such as how data from the ever-growing list of "omics" tools (such as genomics, proteomics and transcriptomics) can be integrated in order to build models of biochemical pathways and mechanisms that will help explain healthy physiology as well as disease.

Researchers across UC San Diego are currently using these types of models, and other advances made possible by systems biology, in order to treat diseases, find new drugs and understand how organisms work at the molecular level.


Read more


    This is a simple introduction to bioinformatics, with a focus on genome analysis, using the R statistics software.

    To encourage research into neglected tropical diseases such as leprosy, Chagas disease, trachoma, schistosomiasis etc., most of the examples in this booklet are for analysis of the genomes of the organisms that cause these diseases.

There is a pdf version of this booklet available at:

other booklet on using R for biomedical statistics,, and my booklet on using R for time series analysis,

ScienceLive guests
Today's Guests (Far left) Michael Eisen is a biologist at the University of California, Berkeley, and a founder of the Public Library of Science. (Second from Left) David Roos is a biologist at the University of Pennsylvania who studies malaria biology and genomics. (Right) John Bohannon and Jon Cohen are contributing correspondents to Science.

By charging authors a fee to publish their research, open-access journals make scientific papers free to the public. But in this new world of academic publishing, journals aren’t always what they appear. Science contributing correspondent John Bohannon went undercover to map out which journals used peer review in evaluating a fatally flawed paper, and he shares his findings in this week’s special science communication issue.
Join Bohannon and two prominent voices in the open-access debate—University of Pennsylvania biologist David Roos and University of California, Berkeley, biologist and Public Library of Science founder Michael Eisen—on Thursday, 10 October, at 3 p.m. EDT on this page to chat about the dark side of open access and the future of academic publishing with Science contributing correspondent Jon Cohen.

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Training the next generation of bioinformaticians

It is essential to train the next generation of bioinformaticians in order to maintain the exceptional quality of bioinformatics in Switzerland. The SIB therefore included the promotion and coordination of Bioinformatics education into its mission. Some of our institute’s members are gathered within the SIB Education Board, where their expertise is used for the organization of a variety of courses, workshops and seminars

View the complete list of this year's events here.
Sign up to remain informed about the education activities at the SIB here.

Forthcoming courses
12 Nov
High Performance Computing (HPC) in Life Science
Bern / Fribourg
21–22 Oct
Best practices in programming 2014
10 Sep
High Performance Computing (HPC) in Life Science
22–27 Jun
Systems Medicine and its applications - and SIB Joint Summer School
9–13 Jun
Advanced statistics - statistical modeling
2–6 Jun
Next Generation Comparative Phylogenomics
21 May
High Performance Computing (HPC) in Life Science
14–17 Apr
Qualitative modelling in the era of big data
7–11 Apr
Genetic Diseases - exome and complete genome sequencing and interpretation
6 Mar
19 Feb
High Performance Computing (HPC) in Life Science
3–7 Feb
Statistical Genomics
25 Nov
Qualitative modelling in the era of big data
20–22 Nov
15 Nov
13 Nov
7 Nov
30 Oct
30–31 Oct
22–23 Oct


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