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mini-workshop on gene network inference, ULg, January 9, 10-12am
by Pierre Geurts 03 Jan '12

03 Jan '12

Dear Colleagues, The Systems and modeling research unit and the GIGA thematic research unit in Systems Biology and Chemical biology have the pleasure to invite you to the following two seminars on gene network inference: Speaker: Robert Küffner, Ludwig-Maximilians-Universität München, Munich, Germany Title: Solutions and Practical Problems in Gene Regulatory Network Inference Date and place: Monday January, 9th 10:00am, Room R7, Institut Montefiore, Sart Tilman, B28, Liège Speaker: Christophe Ambroise, Laboratoire Statistique et Génome, Université d'Évry Val d'Essonne Title: Inferring Sparse Gaussian Graphical Models for Biological Network Date and place: Monday January, 9th 11:00am, Room R7, Institut Montefiore, Sart Tilman, B28, Liège The seminars will be followed in the afternoon by Vân Anh Huynh-Thu's PhD defense: Title: Machine learning-based feature ranking: Statistical interpretation and gene network inference Date and place: Monday January 9th, 2:30pm, Room R3, Institut Montefiore, Sart Tilman, B28, Liège Abstracts and address below. With my best wishes for 2012, Pierre Geurts -- PLACE: Institut Montefiore, Sart Tilman, B28, Liège http://www.montefiore.ulg.ac.be/location.php ABSTRACTS: Speaker: Robert Küffner, Ludwig-Maximilians-Universität München, Munich, Germany Title: Solutions and Practical Problems in Gene Regulatory Network Inference Abstract: The inference of gene regulatory networks from mRNA expression data is characterized by the development of many different approaches with their specific performances, data requirements, and inherent biases. The recent community-wide DREAM challenge conducted a large assessment of inference approaches. The accuracy of predictions was evaluated against experimentally supported interactions in the procaryote model organism E. coli, the eucaryote model organism S. cerevisiae and in silico target systems. Further analysis revealed not only which inference strategies are particularly successful but also which kind of specific information was utilized from the different types of experimental measurements. The challenge evaluation also revealed several weaknesses and limitations of current methods for the generation of artificial datasets as well as the state of the art inference methods. For instance, none of the examined approaches was able to achieve robust predictions from S. cerevisiae data. ----------- Speaker: Christophe Ambroise, Laboratoire Statistique et Génome, Université d'Évry Val d'Essonne Title: Inferring Sparse Gaussian Graphical Models for Biological Network Abstract: Gaussian Graphical Models provide a convenient framework for representing dependencies between variables. In this framework, a set of variables is represented by an undirected graph, where vertices correspond to variables, and an edge connects two vertices if the corresponding pair of variables are dependent, conditional on the remaining ones. Recently, this tool has received a high interest for the discovery of biological networks by l1-penalization of the model likelihood. In this presentation, we introduce various ways of inferring sparse co-expression networks based on partial correlation coefficients from either steady-state or time-course transcriptomic data. All proposals search for a latent structure of the network to drive the selection of edges through an adaptive l1-penalization of the model likelihood. We focus on inference from samples collected in different experimental conditions and therefore not identically distributed. ----------- Speaker: Vân Anh Huynh-Thu, University of Liège Title: Machine learning-based feature ranking: Statistical interpretation and gene network inference Abstract: Machine learning techniques, and in particular supervised learning methods, are nowadays widely used in bioinformatics. Two prominent applications that we target specifically in this thesis are biomarker discovery and regulatory network inference. These two problems are commonly addressed through the use of feature ranking methods that order the input features of a supervised learning problem from the most to the less relevant for predicting the output. This thesis presents, on the one hand, methodological contributions around machine learning-based feature ranking techniques and on the other hand, more applicative contributions on gene regulatory network inference. Our methodological contributions focus on the problem of selecting truly relevant features from machine learning-based feature rankings. Unlike the p-values returned by univariate tests, relevance scores derived from machine learning techniques to rank the features are usually not statistically interpretable. This lack of interpretability makes the identification of the truly relevant features among the top-ranked ones a very difficult task and hence prevents the wide adoption of these methods by practitioners. Our first contribution in this field concerns a procedure, based on permutation tests, that estimates for each subset of top-ranked features the probability for that subset to contain at least one irrelevant feature (called CER for "conditional error rate"). As a second contribution, we performed a large-scale evaluation of several, existing or novel, procedures, including our CER method, that all replace the original relevance scores with measures that can be interpreted in a statistical way. These procedures, which were assessed on several artificial and real datasets, differ greatly in terms of computing times and the tradeoff they achieve in terms of false positives and false negatives. Our experiments also clearly highlight that using model performance as a criterion for feature selection is often counter-productive. The problem of gene regulatory network inference can be formulated as several feature selection problems, each one aiming at discovering the regulators of one target gene. Within this family of methods, we developed the GENIE3 algorithm that exploits feature rankings derived from tree-based ensemble methods to infer gene networks from steady-state gene expression data. In a second step, we derived two extensions of GENIE3 that aim to infer regulatory networks from other types of data. The first extension exploits expression data provided by time course experiments, while the second extension is related to genetical genomics datasets, which contain expression data together with information about genetic markers. GENIE3 was best performer in the DREAM4 In Silico Multifactorial challenge in 2009 and in the DREAM5 Network Inference challenge in 2010, and its extensions perform very well compared to other methods on several artificial datasets.

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Bioinformatics PhD student job opening at Radboud University Nijmegen Medical Centre
by Sacha van Hijum 23 Dec '11

23 Dec '11

Dear all, there is a job-opening for a bioinformatics PhD student at the Radboud University Nijmegen Medical Centre. Closing date: 2nd of October 2011. For those interested, please see below for details. Best regards, Sacha van Hijum Job profile The PhD student will work in a multidisciplinary team with other scientists and medical doctors to discuss, plan and perform bioinformatics research in a highly stimulating environment. Work-place will be the Laboratory of Pediatric Infectious Diseases (Prof. dr. P. Hermans) and the Bacterial Genomics group (Dr. S. van Hijum). • Independently generate and analyze data • Present results at (inter)national scientific meetings and in international peer-reviewed journals Requirements • Msc degree in (molecular) life sciences, specializing in bioinformatics • Background in statistics and understanding of bioinformatics algorithms. Knowledge of Perl/Python and R is a plus • Preferably experience in microbiology, molecular biology and biochemistry • Fluent in English (speaking, reading and writing) • An independent and well-structured working style • Teamplayer and a strong motivation to succeed in scientific and translational research Organization unit Laboratory of Pediatric Infectious Diseases The Laboratory of Pediatric Infectious Diseases at Radboud University Nijmegen Medical Centre is an academic research lab in which scientists and medical doctors work closely together to conduct translational research on the pathogenesis, immunology, and epidemiology of pediatric respiratory tract infections. Our studies aim to increase the molecular and clinical understanding of the interactions occurring between host and pathogen during infection. This knowledge is used to design improved and novel diagnostic, therapeutic, and preventive strategies. The Laboratory of Pediatric Infectious Diseases participates in the Nijmegen Institute for Infection, Inflammation, and Immunity (N4i) and the Nijmegen Center for Molecular Life Science (NCMLS), with focus on basic science and its translation into pioneering treatments for disease. The innovations are advanced through technology platforms such as genomics, proteomics, and molecular imaging. The Laboratory of Pediatric Infectious Diseases works in close collaboration with the… Bacterial Genomics group Focus of the Bacterial Genomics group (Radboud University Nijmegen Medical Centre) is on the bioinformatics analysis of ~omics data of (consortia of) bacteria in the context of industrial fermentations, health and safety. The research involves (meta)genome sequencing and assembly, annotation, comparative genomics, RNA-seq, transcriptomics and multivariate analysis of ~omics datasets, all in relation to exploration and exploitation of the enormous microbial diversity that is found in Nature. The Bacterial Genomics group is part of the CMBI (Centre for Molecular and Biomolecular Informatics). The CMBI pursues a rigorous research program with topics ranging from computational small-molecule chemistry to bioinformatics. The CMBI is among the largest bioinformatics departments in the Netherlands producing dozens of high impact peer-reviewed publications each year. It consists of 4 research groups (Prof. Vriend, Prof. Huynen, Prof. de Vlieg and Dr. van Hijum) with strong connections with the NBiC, centre of excellence and the largest bioinformatics cluster in the Netherlands. Information Prof. dr. P.W.M. Hermans, head of the laboratory, (024) 3666406, P.Hermans(a)cukz.umcn.nl Dr. A.L. Zomer, bioinformatician, (024) 3651545, A.Zomer(a)cukz.umcn.nl Dr. S.A.F.T. van Hijum, group leader Bacterial Genomics (024) 3619389, svhijum(a)cmbi.ru.nl More information and online application via this link: http://www.umcn.nl/OverUMCstRadboud/werkenbij/Pages/Vacature.aspx?VacatureN… -- Dr. Sacha van Hijum Group leader CMBI Bacterial Genomics Group leader Bioinformatics NIZO food research B.V. Bioinformatics coordinator Top Institute Food and Nutrition T: +31(0)318 659 570 F: +31(0)318 650 400 M: +31(0)624782895 E: sacha.vanhijum(a)nizo.nl or svhijum(a)cmbi.ru.nl P.O. Box 20, 6710 BA EDE, The Netherlands Kernhemseweg 2, 6718 ZB EDE, The Netherlands

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molecular epidemiology course in Maastricht
by Lars Eijssen 15 Dec '11

15 Dec '11

Dear colleague, You may find the course below of interest to you or your colleagues. International course on Molecular Epidemiology of Chronic Diseases on April 23 - 27, 2012 in Maastricht, The Netherlands. The Maastricht Molecular Epidemiology Expertise group (M2E2) offers you a challenging five days course (23-27 April 2012) to grasp the essentials of molecular epidemiology. The course brings together the different fields of expertise involved in molecular epidemiological research in a comprehensive and integrated manner. Participants will be confronted with issues such as study design, challenges of incorporating omics data in population studies, statistical analysis of complex data, and interpretation of findings in the context of public health. Focus lies especially on methodological issues, with a variety of disease settings as illustration. The audience targeted is PhD students and postdoctoral fellows from epidemiology, biology, medicine, statistics, and related fields, as well as those working in public health, who want to become acquainted with this expanding research area. Please note that registration will close at 1 February 2012. The number of places is limited. For more information see our website and enclosed flyer. Register through our website: www.M2E2.nl On behalf of the course faculty, Ilja C.W. Arts, PhD and Matty P. Weijenberg, PhD Department of Epidemiology, Maastricht University, Maastricht, The Netherlands Ilja C.W. Arts, PhD Associate Professor Program Nutritional and Molecular Epidemiology ilja.arts(a)maastrichtuniversity.nl www.maastrichtuniversity.nl www.M2E2.nl Peter Debyeplein 1, 6229 HA, Maastricht P.O. Box 616, 6200 MD Maastricht, The Netherlands T +31 43 3882971 F +31 43 3884128 M + 31 6 15623990 For more information: www.M2E2.nl

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FW: job announcement
by Tim De Meyer 12 Dec '11

12 Dec '11

I am leading a small research team in Maastricht, and in co-operation with the dep. of clinical genetics, we have recently obtained a post doc position in oncogenomics (see attachment). The project will be based on the use of Next Generation Sequencing for the identification of additional genetic factors that can modify the cancer risks in carriers of Lynch syndrome mutations. Special focus will be put in Endometrial cancer. Since our expertise on database and bioinformatics analysis is poor, we are looking for candidates who may have some background and experiences in bioinformatics, biostatistics, genetics etc. Therefore, I would like to ask you whether you can let this announcement circulate at your university or if you have any candidate in mind, who may be willing to come over Maastricht for a couple of years. I thank you in advance and I am looking forward to hearing from you. Best, Andrea Romano

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NBIC PhD course Algorithms for Biological Networks
by Celia van Gelder 10 Dec '11

10 Dec '11

*NBIC PhD course Algorithms for Biological Networks* _Date:_ 16-20 January 2012 _Course coordinator_: Dick de Ridder _Location:_ Delft University of Technology, Delft, the Netherlands _Website: _http://www.nbic.nl/education/nbic-phd-school/course-schedule/algorithms-for-biological-networks/__ _Registration:_ http://www.nbic.nl/education/nbic-phd-school/enrolment/ *Target audience//* The course is aimed at PhD students with a background in bioinformatics, computer science or a related field; a working knowledge of basic statistics and linear algebra is assumed. The NBIC Technology Track course"Pattern recognition" and the ASCI course "Advanced pattern recognition" (a1) discuss many of the tools used in this course, but it is not required to have followed these. Prior knowledge of molecular biology is a bonus, but also not strictly required. / / *Course Description //* In this course, we will first give a brief overview of molecular biology, the advent of high-throughput measurement techniques and large databases containing biological knowledge, and the importance of networks to model all this. We will highlight a number of peculiar features of biological networks. Next, a number of basic network models (linear, Boolean, Bayesian) will be discussed, as well as methods of inferring these from observed measurement data. A number of alternative network models more suited for high-level simulation of cellular behaviour will also be introduced. Building on the network inference methods, a number of ways of integrating various data sources and databases to refine biological networks will be discussed, with specific attention to the use of sequence information to refine transcription regulation networks. Finally, we will give some examples of algorithms exploiting the networks found to learn about biology, specifically for inspecting protein interaction networks and for finding active subnetworks. *Course topics * 1. Monday 16-1-2012Networks in biology 2. Tuesday 17-1-2012Network inference 3. Wednesday 18-1-2012 Network enhancement 4. Thursday 19-1-2012 Network validation and execution 5. Friday 20-1-2012 Network mining // / / More information about the course programme can be found on: http://www.nbic.nl/education/nbic-phd-school/course-schedule/algorithms-for… . *NBIC PhD School//* This course is part of the Education Programme of the NBIC PhD School. The NBIC PhD School offers training and education for PhD students in bioinformatics. More information about the NBIC PhD School can also be found on http://www.nbic.nl => Education => NBIC PhD School. *More information//* For more information about the course you can contact Celia van Gelder (NBIC Education) at education(a)nbic.nl. -- Dr. Celia W.G. van Gelder Coordinator Education CMBI Projectleader Education NBIC tel. +31-(0)24-3666120 e-mail: C.vanGelder(a)cmbi.ru.nl websites: www.cmbi.ru.nl, www.nbic.nl Postal address: CMBI 260 Radboud University Nijmegen-Medical Centre /NCMLS PO Box 9101, 6500 HB Nijmegen The Netherlands

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Probabilistic Graphical Models 2012 Call for Papers
by Manuel Gómez Olmedo 02 Dec '11

02 Dec '11

Probabilistic Graphical Models (PGM2012) Workshop Granada, Spain, 19-21 September 2012 (http://leo.ugr.es/pgm2012) Call for papers The aim of the workshop is to bring together people interested in probabilistic graphical models and provide a forum for discussion of the latest research developments in this field. The workshop is organized so as to facilitate discussions and collaboration among the participants also outside the workshop sessions. To facilitate the spreading of research results and promote the interactions among all participants, parallel sessions will be avoided, organizing the conference around plenary and posters sessions. We welcome theoretical and applied contributions related to the following topics: * Principles of Bayesian (belief) networks, chain graphs, decision networks, influence diagrams, and other probabilistic graphical models (PGMs). * Information processing in PGMs (exact and approximate inference). * Learning and data mining in the context of PGMs: machine learning approaches, statistical testing and search methods, MCMC simulation. * Exploitation of results from related disciplines for the construction of PGMs, e.g., statistics, information theory, optimization, decision making under uncertainty, multivariate statistical analysis. * Software systems based on PGMs. * Application of PGMs to real-world problems. We invite submissions that concern one or more of the above topics, or any other aspects related to probabilistic graphical models. Papers submitted for review should report on original, previously unpublished work. Each submitted paper will be reviewed by at least two reviewers. Submission procedure PGM 2012 requires electronic submission of papers according to the instructions found on the page with author instructions <http://leo.ugr.es/pgm2012/author-instructions.php>. The authors must prepare their papers according to the PGM proceedings format, and submit the full version of the papers by the deadline found below. The page limit is 8 pages, including figures and bibliography. The page for author instructions contains format information and provides access to style files and templates. Papers will be accepted for plenary or poster presentation. All accepted papers will be included in the proceedings (with ISBN), which will be made available at the workshop reception. At least one author of accepted papers is expected to attend the workshop. After the workshop, authors of selected papers will be invited to submit an extended version of their paper to appear in a special issue of a high quality journal. All of the submitted papers will undergo a full reviewing process. Important Dates Call for papers opened November 2011 Deadline for abstract submissions April 27, 23:59 GMT, 2012 Paper submissions May 4, 23:59 GMT, 2012 Notification of acceptance June 29, 2012 Final versions due August 17, 23:59 GMT, 2012 Welcoming reception September 18, 2012 Workshop dates September 19-21, 2012 -- Manuel Gomez Olmedo e-mail: mgomez(a)decsai.ugr.es Dpto. de Ciencias de la Computacion e Inteligencia Artificial E.T.S. Ingenierias Informatica y de Telecomunicacion Universidad de Granada Tel.: +34 958 246143 18071 - GRANADA (Spain) Fax: +34 958 243317

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Mathematical and Computational Evolutionary Biology (18-22/06/2012)
by Guy Baele 01 Dec '11

01 Dec '11

-------- Message original -------- Sujet: [bioinfo] Mathematical and Computational Evolutionary Biology (18-22/06/2012) Date : Wed, 23 Nov 2011 20:18:16 +0100 De : Gascuel Olivier <gascuel(a)lirmm.fr> Pour : bioinfo(a)sfbi.fr PLEASE DIFFUSE THIS ANNOUNCEMENT. THANKS! Mathematical and Computational Evolutionary Biology June 18-22, 2012, Hameau de l'Etoile (France) http://www.lirmm.fr/mceb2012/ The subject is evolution, which is considered at different scales, from genes to populations. The focus is on the mathematical and computational tools and concepts, which form an essential basis of evolutionary studies. The meeting will bring together researchers originating from various disciplines: mathematics, computer science, phylogenetics and population genetics. Ten keynote speakers will introduce a field of research and discuss their own work in this field. Afternoon will be for short presentations and posters, with plenty of time for discussions, hiking and visits. The number of attendees will be limited (~60) to favor exchanges. The meeting will take place at Hameau de l'Etoile, in the Montpellier region (France). The dates are June 18-22, that is, just before SMBE 2012 that starts June 23 in the evening at Dublin (Ireland). Conference fees including accommodation (4 nights, 18 to 22), meals, coffee breaks, buses, etc., will range from ~350 EUR to ~500 EUR depending on the room type. Keynote speakers: Michael Blum (CNRS - TIMC, FR). Oliver Eulenstein (Iowa State University, US). Arnaud Estoup (INRA - CBGP, FR). Vincent Moulton (University of East Anglia, UK). Rasmus Nielsen (Berkeley, US). Noah Rosenberg (University of Michigan, US). Alexandros Stamatakis (Heidelberg, DE). Mike Steel (University of Canterbury, NZ). Edward Susko (Dalhousie University, CA). Simon Tavaré (Cambridge University, UK). Organizers: Olivier Gascuel Jean-Michel Marin See the web site for more details and pre-registration #################################################################### -- http://www.sfbi.fr Archives : http://listes.sfbi.fr/wws/arc/bioinfo ####################################################################

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FW: Postdoctoral positions
by Tim De Meyer 29 Nov '11

29 Nov '11

Postdoc position (epigenetics computational biology) in Milan, apologies for double posting. From: Wim Vanden Berghe [mailto:wimk.vandenberghe@gmail.com] Sent: maandag 28 november 2011 17:38 To: Tim De Meyer; Wim Van Criekinge Subject: Fwd: Postdoctoral positions interessant voor kandidaten bij jullie? IFEO campus labo is zeer sterk in chip seq op primaire stalen, wim ---------- Forwarded message ---------- From: Gioacchino Natoli <gioacchino.natoli(a)ifom-ieo-campus.it> Date: 2011/11/28 Subject: Postdoctoral positions To: gioacchino natoli <gioacchino.natoli(a)ifom-ieo-campus.it> Dear Friends and Colleagues, Attached please find an ad for two postdoc positions in my lab. I would very much appreciate if you could forward it to your contacts or directly refer to me any suitable applicant. Thanks a lot for the help! Best regards, -Gioacchino Gioacchino Natoli MD Department of Experimental Oncology European Institute of Oncology Campus IFOM-IEO Via Adamello, 16 20139 Milan, Italy tel +39-0257489-953 <tel:%2B39-0257489-953> <http://www.ifom-ieo-campus.it/research/natoli.php> http://www.ifom-ieo-campus.it/research/natoli.php http://www.semm.it/education.php -- Wim Vanden Berghe, Prof. Dr. Department Biomedical Sciences - University Antwerp PPES lab Protein Science, Proteomics & Epigenetic Signaling Campus Drie Eiken, T1.35 Universiteitsplein 1 2610 Wilrijk _____ Geen virus gevonden in dit bericht. Gecontroleerd door AVG - www.avg.com Versie: 2012.0.1873 / Virusdatabase: 2101/4643 - datum van uitgifte: 11/27/11

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Python courses
by Karolis Lesickas 16 Nov '11

16 Nov '11

Dear all, We are planning a new series of beginners courses in python programming in Vilnius: Beginner's course: Python Programming for Structural Bioinformatics <http://www.spronknmr.eu/courses/bioinformatics/beginners-course-python-prog…> Beginner's course: Python Programming for Structural Bioinformatics <http://www.spronknmr.eu/courses/bioinformatics/beginners-course-python-prog…> *Course dates* * November 29 - 30, 2011 <http://www.spronknmr.eu/marketplace/timeline/576> * February 02 - 03, 2012 <http://www.spronknmr.eu/marketplace/timeline/644> * February 13 - 14, 2012 <http://www.spronknmr.eu/marketplace/timeline/646> * March 05 - 06, 2012 <http://www.spronknmr.eu/marketplace/timeline/777> * April 09 - 10, 2012 <http://www.spronknmr.eu/marketplace/timeline/778> * May 07 - 08, 2012 <http://www.spronknmr.eu/marketplace/timeline/779> The course is intended for novices in programming, and provides a solid basis to automate workflows involving large amounts of different data types, which are typical in structural bioinformatics. Basic programming concepts are introduced in lectures, and practiced on examples using real data. For further information you can have a look at the course website here <http://training.spronknmr.eu/index.php?mact=Courses,cntnt01,frontend_catego…>. To sign up, students should not make use of the website, but send an email to Karolis Lesickas (karolis.lesickas(a)spronknmr.eu <mailto:karolis.lesickas@spronknmr.eu>). He will then make the further arrangements. Kind regards, Karolis

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Workshop on Genomics + Galaxy and Advanced Topics, January, Czech Republic
by Dave Clements 12 Nov '11

12 Nov '11

*2012 Workshop on Genomics * Český Krumlov, Czech Republic 8-25 January 2012 http://evomics.org/ The 2012 Workshop on Genomics covers various aspects of genomics focusing primarily on the analysis of next-generation sequencing data. With the addition new events, including a Galaxy Developers Workshop, and several multi-day Advance Topics courses, the 2012 Workshop is greatly expanded over previous years. ** Please see the event pages for more details and* please note that the preferred deadlines for these events are rapidly approaching!* * Core Workshop on Genomics: * 15 Nov 2011 Application review starts 8-21 Jan 2012 Workshop http://evomics.org/workshops/workshop-on-genomics/2012-genomics-cesky-kruml… *Advanced Topics Sessions: ** Programming with Python/Biopython for Genomic Data Analysis GMOD (GBrowse, JBrowse, WebApollo, Chado) Using R and Bioconductor to Analyze Genomic Data** * 15 Nov 2011 Application review starts 23-25 Jan 2012 Courses http://evomics.org/workshops/advanced-topics/ *Galaxy Developer Workshop: 23 January 2012 * 15 Dec 2011 Registration deadline 23 Jan 2012 Workshop http://evomics.org/workshops/galaxy-developer-workshop/ -- <http://evomics.org/workshops/galaxy-developer-workshop/> http://getgalaxy.org http://usegalaxy.org/ http://galaxyproject.org/wiki

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