Information for existing EBI predocs - Predoc training

Dates: 17-19 January 2011
Venue: IT-Training Room, East Wing at the EBI
Scientific Organisers: James Watson, Vicky Schneider
Admin and Logistics: Tracey Andrew, Kathryn Hardwick

I studied Genetics and Molecular Biology, for both my bachelor and masters, at Faculty of Sciences - University of Lisbon. My training was therefore bench-orientated, but an introductory course of Bioinformatics made me realise that this was the field I wanted to study. Since then I have learned the basics of Perl and C and developed some work in Python and Awk, but I am really enthusiastic about the possibility of improving my programming skills.

In my master thesis, at Institut Pasteur, I worked in comparative genomics of Integrative and Conjugative Elements (ICE) in all the prokaryotic genomes available. Working with eukaryotic genomes and analysing microRNA data from next-generation sequencing will be an exciting new challenge.

I studied Bioinformatics at the University of Glasgow. During the course of the master's programme I have developed a strong interest in Java and Perl programming. My original curiosity for bioinformatics developed during an internship for my undergraduate study. My primary task was to search for - and subsequently experimentally test - inhibitors for D-amino acid oxidase using open-source virtual screening software and other in silico techniques.

For my master's thesis I investigated drug target properties in the human protein-protein interaction network. The work gave me a first, very basic understanding of network analysis and its applications.

Based on my background in pharmaceutical chemistry, largely focussed on wet lab analytical chemistry, I am enthusiastic about the emerging possibilities in the field of chemoinformatics, combining both areas of interest -- programming and chemistry.

I've studied Biochemistry at the University of Lisbon, Portugal, and later on I took a master degree in Drug Discovery and Safety, with a specialization in Computational Medicinal Chemistry and Toxicology at the Vrije Universiteit Amsterdam, Netherlands. During my master, my main research was to investigate the role of water molecules in molecular docking simulations of the human cytochrome P450 2D6, since including water molecules in computational approaches for drug design or site-of-metabolism predictions is currently far from straight forward.

Lately, I've been working both at MedILS in Split, Croatia and at Max F. Perutz Laboratories in Vienna, Austria, in cellular organization, more specifically can proteins self-organized based solely on their physical properties, and with that, can we predict their neighbours?; and ultimately design a more selective drug?

My main scientific interested are then, explore new methods/ideas on how to speed up the discovery of new medicines and improve its safety. During my research I've used primarily python, but also c++, Fortran 66, and a bit of R. I would, therefore, like to expand and improve my programming skills.

I graduated from the University of Birmingham in 2010 having read a BSc in Biology with Computing (Bioinformatics). During my degree, I undertook a fourteen month placement in the Advanced Protein Technologies team of Lonza Biologics plc located in Cambridge. My placement involved research and development of an algorithm for the prediction of non-native protein-protein interactions. The project involved applying computational analysis of biochemistry and 3D structure to identify problematic regions in proteins. The algorithm was developed to identify potentially problematic traits in therapeutic manufacture, before large scale production proceeded.

The research in my final year of University was developing a web-tool written in Poerl and C++. The tool was able to speed up analysis of structural alignment results by adding annotations and automating additional protocols. This work helped identify important neighbours of a cell envelope construction enzyme and potential drug target in M. tuberculosis.

I have also studied statistical analysis of microarrays, utilising this in discovery of biomarkers in muscular dystrophies and diabetes. I have experience in a variety of different computer languages including Perl, R, Java, C++ and Objective-C. My current interests are in modelling biological systems (i.e. metabolic) and probing these systems for beneficial alterations. I am applying my knowledge of biochemistry and statistical analysis to metabolomics network reconstruction at EBI.

I'm from Granada (Spain), my main background is chemistry but I have strong interests in biological and computational areas. Combination of wet and dry lab training composed the five years of my undergraduate studies, by the time, I also learned basic programming in C++, bash scripting and Mathematica.

During the last two, I took part in several experimental and theoretical research projects which covered diverse scientific areas ranging from (in order of occurrence) DNA Nanotube Mechanics, protein folding dynamics, drug design & network biology of autoimmune and neurodegenerative diseases, respectively. Applied techniques were as diverse as epifluorescence microscopy, molecular dynamics simulations and docking. The last one was completed from July to October 2010 at Aloy's group in IRB Barcelona and it was focused on extending the current map of Parkinson's Disease molecular biology by curating structural and genetic information from literature and public databases. During this period I also gained confidence with Python language.

Previous training in conjunction with future improvement of programming skills will be the starting point for PhD research in basic principles of enzyme structure and function in metabolic networks.

I did my undergraduate study on biology at the Department of Life Science in Wuhan University, China, where I enjoyed a wide range of courses and trainings offered by the four year program. From my 3rd year I worked as an intern at the Modern Virology Research Centre and AIDS Centre, China and looked at BIV mediated cell fusion, and the immunogenicity of HCV vaccines based on two different viral vectors. After graduation with biology degree, I went to pursue an MSc in Bioinformatics at the University of Edinburgh driven by my strong interests in computational approaches and their applications in biology. I came to Cambridge after my MSc and worked on the METABRIC project, a large scale genomics effort in breast cancer, in Professor Caldas's group at the CRI. I was involved in developing database and system solutions for such study. During my time at the CRI I found myself mostly enjoyed working on the interface among biology, statistics and informatics. With my PhD at the Sanger, I hope to continue working on this interface and exploring approaches to transform large volumes of data into information and knowledge.

Mar Gonzalez-Porta (EBI): My training has been mainly focused on Life Sciences, since I studied a degree in Biotechnology in University Rovira i Virgili in Tarragona, Catalunya (Spain). However, my interest for Bioinformatics arose very early during my degree, and since then, subjects related with Computer Science have been the perfect excuse to continue acquiring computing skills. At the present moment I have some knowledge about different programming languages (MySQL, Perl, Unix shell scripting, R and web design - HTML and CSS) but I would really like to improve my skills in the early future.

In parallel with my studies, I was collaborating with a Bioinformatics research group from my university in a project related with Epigenetics and Nutrigenomics. I also did a placement in the Swiss Institute of Bioinformatics (SIB, Lausanne) as part of my Diploma thesis, which was centered on the study of miRNA expression and function from an evolutionary point of view. Finally, this summer I have been working in the Center for Genomic Regulation (CRG, Barcelona) on a Bioinformatics project about variability in gene expression and alternative splicing between individuals.

My scientific interests cover a range of issues related with Bioinformatics. I see this discipline as a tool both to deal with the huge amount of experimental data available nowadays and to define the path to follow in the laboratory. In particular, I am interested in the use of this discipline to bring a lot of different data together to gain deeper knowledge of a topic.

I am a medic currently doing a PhD on the Wellcome Trust Clinical PhD programme. My undergraduate degrees were in physiological sciences and medicine from the University of Oxford. My area of specialty is medical microbiology and I undertook a part-time MSc in clinical microbiology at the University of Nottingham during my hospital training. My research at the Sanger Institute involves the study of bacterial pathogenesis focusing on invasive Salmonella disease. Part of my PhD will use the information generated from a range of genetic approaches to investigate what makes particular species of Salmonella more virulent in terms of their ability to cause disease, than others. I have no previous experience of bioinformatics, and I hope to learn a range of computer science skills that will not only help me address pertinent questions during my PhD, but also provide me with lifelong knowledge for future work in my academic career.

Studies: My first step was a Master in Biochemistry from the University in Geneva (Switzerland). I decided to do the Master in Bioinformatics and Proteomics of the Swiss Institute of Bioinformatics before directly starting a PhD over-there.

Work: I have done internships in two pharmaceutical companies: Bracco Research, by doing the development of a technique called sonoporation (drug and gene delivery experimental method) and in Addex Pharmaceuticals, an industry focused toward discovery of allosteric compounds. I have worked in an NGO: Health On the Net. I visited Glasgow (UK) for my Master thesis in bioinformatics. I was working on the realization of a small program helping for protein quantification by mass-spectrometry.

PhD Project: I'm in the European Bioinformatics Institute (EBI) working in the group of Dietrich Rebholz-Schuman (text-mining). The formal title of my PhD is 'Representation of semantic relations in the Semantic Web based on ontological support: inference of gene-disease association from the literature and biomedical data resources'. In other words, I will be using ontologies to make some knowledge discovery from scientific databases (Uniprot, InterPro, etc...) and the literature.

My main background is molecular biology and bioinformatics. I did my bachelor's degree on genome sciences in Mexico, where I had courses on biology, mathematics and statistics and became familiar with several programming languages such as Perl, C and R and worked a little bit with MySQL and PHP. During my final year I gained some teaching experience and worked on a mathematical model that could predict a cell's response to changes in extracellular concentrations of nickel. After graduation I worked in two laboratories where I could do some wet lab work and learn several experimental techniques such as flow cytometry, microscopy, tissue culture and mice handling. At the moment, I am interested in the discovery of novel genes implicated in cancer origins and progression as well as in the creation of models that can explain these processes to a certain extent. During my PhD I expect to improve my skills in these tools and learn many others in order to make a valuable contribution to our current understanding of cancer development.

I obtained my Bachelor's and Master's in bioengineering from the Universit' Libre de Bruxelles (Belgium). My Master's thesis was focused on studying the mechanisms of corticogenesis in mammals using mouse embryonnic stem cells. I also did an applied research project in computational fluids dynamics.

Following this, I did an Mphil in Computational Biology at the University of Cambridge, in an attempt to combine my biological and mathematical/engineering interests. This Master's included a 3 months research project during which I developped an R/Bioconductor package for gene set and network analysis of large scale RNAi data sets. I applied these and other networks methods to investigate genetic interactions with BRCA2 in order to have a better understanding of its functions and involvement in breast cancer.

During my PhD, I am going to look into developping a modelling framework for signalling and regulatory networks that can accomodate heterogeneous biological knowledge. This could in turn be applied to the analysis of biochemical data related to various human diseases. This project would combine my engineering and biomedical skills at it would consist of modelling work conducted in close collaboration with various experimental labs.

I first studied Mathematics at the University of Cambridge and after developing an interest in Mathematical Biology I decided to do an MPhil in Computational Biology.

I have completed two short research projects, one in the field of functional genomics looking at the effect of annotation on microarray results, and another in statistical genetics looking at the effect of cryptic population structure on population linkage analysis.

Having completed computer projects for both my maths degree and my masters I am competent in C and R and have also used MATLAB and perl.

I am interested in evolutionary biology and will be looking at the impact of next generation sequencing technology on the comparative analysis of genomic sequences. The work will be computationally based with novel data coming through collaborations including multi-national consortia.

I have a double background in Biotechnologies and computer science. After two years of Maths sup / Maths sp' in Paris, I entered an Grande Ecole for three years in Toulouse (ENSAT) where I obtained a master degree specialized in Biotechnologies. I had the chance to combine the last year of my school with a specialized master's degree in another Grande Ecole (ENSEEIHT) providing me with a double diploma in Computer Science.

I am very interested in the challenges that high throughput sequencing, especially single cell sequencing offers to computer scientists. Indeed, to make sense of such a huge amount of data, the algorithms have to be constructed on very efficient statistical methods that capture as much information as possible in order to answer relevant biological questions. This field is very challenging because it is highly multidisciplinary combining state of the art methods in biology, computer science and applied mathematics.

I completed an undergraduate degree in computer science at Neumont University and worked for a few years as a technology strategy consultant at IBM and Deloitte Consulting. Simultaneously with my work at Deloitte, I was also remotely working for a biomedical lab at the Harvard Medical School. My research there was focused on the connection between basal transcription initiation and the non-linear breathing dynamics of DNA. Being part of a biomedical research lab showed me that I am passionate about uncovering the enigmas hidden in biology which lead me to pursue furthering my education. I just finished an MPhil in computational biology at the University of Cambridge and I am currently doing a PhD at the Wellcome Trust Sanger Institute. My first rotation project is focused on examining the genomics in the transmissible cancer in Tasmanian devils.

My background is Computer Science. I have ever worked on some large-scale projects and later participated in the development of BioModels Database. Since then, the practical questions in life science attracted my attention.

My research work will use Natural Language Processing, statistics and text mining to look for causative effects of recorded gene-disease associations. Initially, a solution will be developed to distinguish factual from hypothetical statements (training material available). The scientific literature will then be mined for statements reporting on the positive/negative regulation of molecular, cellular, biochemical, hormonal and physiological processes (exploiting the Whatizit infrastructure). Identified statements will be classified for their evidence and the relevance to a given disease (contextual analysis). Evidence for the same processes will be gathered from public bioinformatics data resources: Kegg, UniProt, Reactome, IntAct, even if the disease relevance is not given. The ensemble of events will be loaded into a triple store for public data access and data analysis. The relations between the entities will be defined using the standards from the Relation Ontology (RO). Different inference solutions will be evaluated to evaluated the relevance of infer up- or downregulation of a cellular component or a tissue from molecular, hormonal or drug-induced up- or down regulation of biochemical processes.

I come from a computer science background. I finished my master's degree at the Budapest University of Technology and Economics, where my research focus was mobile agent systems. I also have a fair amount of professional experience working for Nokia and Microsoft Research, where I did various research projects, such as pedestrian navigation, sensor networks or robotics.

Biology is something that has enticed and inspired me ever since the Human Genome Project has been completed, which has made advances possible that were previously unimaginable. In my spare time I started to attend courses on the MIT OpenCourseWare and started my own pet project; GenDiff: a differential compression tool for genetic data. I am very keen on learning more about biology and find areas, where computer science techniques can truly advance the state of the art.

Areas of interest: gene regulation, computer algorithms, molecular computation

I completed my undergraduate degree in statistics and genetics from the University of Queensland in 2009, after which I was employed as a research assistant at the Queensland Institute of Medical Research. There, I worked on genome-wide association studies (GWAS) for a variety of traits and diseases including melanoma, glaucoma and smoking behaviour. I was also involved in developing novel methods for post-GWAS analysis using gene and pathway-based approaches. I began my PhD at the Wellcome Trust SangerInstitute in October 2010.

My primary interest is in statistical genetics. While GWAS have successfully identified hundreds of common genetic variants associated with a variety of complex traits and diseases, for the majority of cases, these variants explain only a fraction of total heritability. The remaining heritability is likely to come from a combination of common variants with even smaller effects and rare variants - for which current GWAS methods are underpowered to detect. New statistical challenges will arise as we move beyond GWAS and towards whole-genome sequencing of thousands of individuals to identify these rare genetic variants that make us susceptible to disease. I generally use Perl, R and shell scripting.

I recently finished my undergraduate degree double majoring in biology and computer science at Earlham College.  I have spent the last six months working on a project for mapping cerebrospinal fluid protein data to dynamically generated protein interaction graphs.  I am working at the EBI for six months updating and improving PICR.  I am currently looking for graduate programs and am interested in seeing if the EBI would be a good fit for a PhD program.