- BBClist - maillist.psb.ugent.be

Postdoc position at University of Pretoria
by Ridder, Dick de 10 May '16

10 May '16

FYI: The Fruit Tree Biotechnology Programme (FTBP) at FABI, University of Pretoria has a research position available for a bioinformatician. Our established research programme is funded by the Hans Merensky Foundation and focuses on the understanding of tolerance and pathogenicity in the avocado-Phytophthora cinnamomi system. Description: the successful candidate will be responsible to manage the AvoGenome project by initiating and leading projects in the field of genomics of both avocado and P. cinnamomi. Duties include (but are not limited to): - Perform quality bioinformatics analysis of high throughput genomic data and assist in the interpretation of analyzed data - Conceive and develop bioinformatics tools and processes in order to analyze large scale datasets - Initiate new projects and work independently on a variety of bioinformatics analysis projects. - Manage databases, conduct statistical and genomic analysis, and participate in the preparation of manuscripts and presentations. - Collaborate with wet-bench biologists to analyze data derived from projects using high-throughput sequencing and microarrays. - 3-5 year contract. Requirements: - PhD in bioinformatics, biostatistics, genomics (or similar) - Experience with scripting in R, Python or Perl (etc.), biological datasets and statistics - Excellent communication skills, strengths in problem-solving and creative thinking - Extensive knowledge in bioinformatics, proven by a record of scientific publications in bioinformatics and/or genomics journals - Candidate with dual background in both computation and biology will be advantageous HOW TO APPLY: - Send a cover letter and CV to: Prof. Noëlani van den Berg (noelani.vdberg(a)fabi.up.ac.za)

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'STATS COURSE - Genetic data analysis/exploration using R'
by Oliver Hooker 10 May '16

10 May '16

"Genetic data analysis/exploration using R" Delivered by Dr. Thibaut Jombart http://prstatistics.com/course/genetic-data-analysis-using-r-gdar/ This course will run from 16th – 20th August, Millport Field Station, Ilse of Cumbrae, Scotland This course will provide an extensive overview of exploratory methods for the analysis of genetic data using the R software and aim to equip participants with powerful resources for tackling increasingly common challenges in genetic data analysis. It is aimed at PhD students, research postgraduates, and practicing academics as well as persons in industry working with genetic data in fields such as molecular ecology, evolutionary biology, and phylogenetics. This course will provide a comprehensive introduction to various statistical approaches for the analysis of genetic data. Course content is as follows Day 1 Introduction to phylogenetic reconstruction • Lecture 1a: Reconstructing phylogenies from genetic sequence data. Three main approaches covered: distance-based phylogenies; maximum parsimony; and likelihood-based approaches. • Lecture 1b: Short R refresher. • Practical 1: Phylogenetic reconstruction using R. Three main approaches plus rooting a tree; assessing/testing for a molecular clock; and bootstrapping. Main packages: ape, phangorn. Day 2 Introduction to multivariate analysis of genetic data • Lecture 2: Key concepts in multivariate analysis. Focus on using factorial methods for genetic data analysis. • Practical 2: Basics of multivariate analysis of genetic data in R. Topics include: data handling, population genetic tests of population structure (PCA, PCoA). Main packages: adegenet, ade4, ape. Day 3 Exploring group diversity • Lecture 3: Approaches to identifying and describing genetic clusters. Topics include: hierarchical clustering, K-means, population-level multivariate analysis (between-group-PCA, DA, DAPC). • Practical 3: Applying the approaches covered in morning lecture and emphasising their strengths and weaknesses. Main packages: adegenet, ade4. Day 4 Spatial genetic structure • Lecture 4: Discussing the origin and significance of spatial genetic patterns, and how to test or them. • Practical 4: Visualising and analysing spatial genetic data. Topics: spatial density estimates, Moran/Mantel tests, mapping principal components in PCA, spatial PCA. • Main packages: adegenet, glmnet. Main packages: adegenet, glmnet. Day 5 Using R for reproducible science • Lecture 5: Using R for reproducible science. • Practical 5: Practical session based on morning lecture • Main packages: knitr, Sweave, rmarkdown • Option to discuss own data (time permitting) Please email any inquiries to oliverhooker(a)prstatistics.com or visit our website www.prstatistics.com Please feel free to distribute this material anywhere you feel is suitable Upcoming courses - email for details oliverhooker(a)prstatistics.com ADVANCING IN STATISTICAL MODELLING USING R (May) TIMES SERIES DATA ANALYSIS FOR ECOLOGISTS AND CLIMATOLOGISTS (May) INTRODUCTION TO PYTHON FOR BIOLOGISTS (May) ADVANCES IN SPATIAL ANALYSIS OF MULTIVARIATE ECOLOGICAL DATA (July) ADVANCES IN DNA TAXONOMY USING R (August) INTRODUCTION TO BIOINFORMAITCS USING LINUX (August) INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (August) MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R (October) LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (October) APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS (October) PHYLOGENETIC DATA ANALYSIS USING R (November) SPATIAL ANALYSIS OF ECOLOGIC AL DATA USING R (November) Dates still to be confirmed - email for details oliverhooker(a)prstatistics.com STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R INTRODUCTION TO R AND STATISTICS FOR BIOLOGISTS BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS Oliver Hooker PR statistics 3/1 128 Brunswick Street Glasgow G1 1TF +44 (0) 7966500340 www.prstatistics.com www.prstatistics.com/organiser/oliver-hooker/

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Still seats available for the BioSB course: Algorithms for Biological Networks (4th edition), May 23-27 2016, Delft
by Femke Francissen 10 May '16

10 May '16

*Still seats available for BioSB Course: Algorithms for Biological Networks (4th edition)!* *General course information* *Date: * 23-27 May 2016 *Course coordinators:* Dick de Ridder (WUR), Jeroen de Ridder (TUD) *Location:* Delft University of Technology (TUD), Delft, the Netherlands Website <http://biosb.nl/education/course-portfolio/course-algorithms-for-biological…> Registration <http://biosb.nl/education/course-portfolio/course-algorithms-for-biological…> *Target audience* PhD students with a background in bioinformatics, computer science or a related field; a working knowledge of basic statistics and linear algebra is assumed. *Course description* In the fourth edition of 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 networks from observed measurement data and of integrating various data sources and databases to refine networks. Once networks are derived they often serve as the cornerstone in the visualization, analysis and interpretation of high-throughput data; we will discuss a number of methods in this area. As an alternative to static networks, a number of alternative dynamic network models more suited for high-level simulation of cellular behaviour for will be introduced. 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 sub networks. *Course programme* The course website, including full course programme, can be found at http://helix.ewi.tudelft.nl/nbic/abn/. *BioSB Education Programme* This course is part of the Education Programme of BioSB, the Netherlands Bioinformatics and Systems Biology research school, which offers training and education for in bioinformatics and systems biology. More information about BioSB can be found at www.biosb.nl.

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[Gtpb] GTDA16 Genomic and Transcriptomic Data Analysis - Announcement/Reminder
by Pedro Fernandes 09 May '16

09 May '16

ANNOUNCEMENT / REMINDER (Last days to decide to apply) Applications for GTDA16 - Genomic and Transcriptomic Data Analysis with Francisco García and Alejandro Alemán are open. Candidates with adequate profile will be accepted in the next 72 hours after the application until we reach 20 participants. This is a relatively short but very effective way of providing skills in NGS data analysis using online tools. Target audience The course is oriented to experimentalists, end-users and graduate students who want to learn about state-of-the-art data analysis methodologies in this fast developing area. Students will acquire the necessary skills for analysing their own data using known software packages. Description Course Description This is a 3 day long theoretical and practical course on genomic data analysis. Questions such as How can I find the causative mutation of the disease in this family? What pathways are activated in my RNA-seq experiment? are becoming more frequent as Next Generation Sequencing (NGS) technologies are increasingly used in the laboratory. This activity has been designed to provide the researchers with the skills and tools to address these questions and many other ones related. The whole course is composed of two group of sessions that focus on the analysis of Genomic variation and Transcriptomics of Next Generation Sequencing Data. The genomics sessions review the different NGS technologies and their applications as well as the computational requirements of NGS-based projects. Following an introduction to NGS of genomes, exomes and panels, attendants will learn about NGS data quality issues, data pre-processing, how to compare sequenced reads with a reference genome and how to visualize the results in a genomic context. Then, the main aspects of genomic variant annotation, detection and prioritization of candidate variants will be covered. State-of-the-art software to assist in gene prioritization process will be used. Finally, NGS in the clinic will be reviewed with the use of panels of genes for precision diagnostic and the management of variants of uncertain effect. The transcriptomics sessions is devoted to transcriptomic studies (RNA-seq and miRNA-seq). After an introduction to NGS of transcriptomes, the attendants will learn to perform all the preprocessing steps to convert NGS reads into gene expression measurements. Then, gene expression data will be used to determine differential expression, to cluster expression patterns, or for building predictors. Functional profiling methodologies will be used to interpret the results according to gene ontology enrichment, network analysis, etc. Finally, sophisticated methods for pathway analysis of transcriptome profiles will be demonstrated. The Babelomics suite, a well-known package of gene expression analysis, will be used to illustrate. By the end of the course, participants will have acquired skills to interpret NGS data and to use multiple software tools for genetic variant detection and for transcriptomic studies. More details at the GTPB website http://gtpb.igc.gulbenkian.pt/bicourses/GTDA16/ Best wishes Pedro Fernandes -- Pedro Fernandes GTPB Coordinator Instituto Gulbenkian de Ciência Apartado 14 2781-901 OEIRAS PORTUGAL Tel +351 21 4407912 http://gtpb.igc.gulbenkian.pt _______________________________________________ GTPB mailing list GTPB(a)igc.gulbenkian.pt https://lists.igc.gulbenkian.pt/mailman/listinfo/gtpb

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Extended deadline META'2016
by El-ghazali Talbi 09 May '16

09 May '16

Apologies for cross-posting. Appreciate if you can distribute this CFP to your network. ********************************************************************** META'2016 International Conference on Metaheuristics and Nature Inspired Computing 27-31 Oct 2016 Marrakech, Morocco http://meta2016.sciencesconf.org/ ********************************************************************** META is one of the main event focusing on the progress of the area of metaheuristics and their applications. As in previous editions, META’2016 will provide an opportunity to the international research community in metaheuristics to discuss recent research results, to develop new ideas and collaborations, and to meet old friends and make new ones in a friendly and relaxed atmosphere. META'2016 welcomes presentations that cover any aspects of metaheuristic research such as new algorithmic developments, high-impact applications, new research challenges, theoretical developments, implementation issues, and in-depth experimental studies. META'2016 strives for a high-quality program that will be completed by a number of invited talks, tutorials, workshops and special sessions. The scope of the META’2016 conference includes, but is not limited to: * Local search, tabu search, simulated annealing, VNS, ILS, … * Evolutionary algorithms, swarm optimization, scatter search, … * Emergent nature inspired algorithms: quantum computing, artificial immune systems, bee colony, DNA computing, … * Parallel algorithms * Hybrid methods with machine learning, game theory, mathematical programming, constraint programming, co-evolutionary, … * Application to: logistics and transportation, networks, scheduling, data mining, engineering design, energy, cloud, bio-medical, … * Theory of metaheuristics, landscape analysis, convergence, problem difficulty, very large neighbourhoods, … * Multi-objective optimization, bi-level optimization * Dynamic optimization, problems with uncertainty, … * Parameter tuning (static, dynamic, adaptive, self-adaptive) * Hyper-heuristics, cross-domain metaheuristics * Software frameworks for metaheuristics and nature inspired computing Submission of papers: ____________________ - Submission of papers via the website S1) Short papers: Extended abstracts of work-in-progress and position papers of a maximum of 3 pages. S2) Long papers: Original research contributions of a maximum of 10 pages. S3) Journal papers: High-quality manuscripts that have recently, within the last year, been submitted or accepted for journal publication. For this special case, the submission should have the same title that the accepted work, the abstract AND the complete reference of the work. - Proceedings of the conference will be provided. Selected papers of type S1 and S2 will be published in a Springer book and international journals (ISI journals). - Predefined styles are available on the website http://meta2016.sciencesconf.org/ - Proposals for invited sessions, workshops and tutorials: Deadline 15th April 2016. contact el-ghazali.talbi(a)univ-lille1.fr Important dates _______________ - Extended Submission deadline: May 27, 2016 - Notification of acceptance: June 3, 2016 E-G. Talbi (Conference Chair) -- ********************************** META'2016 Marrakech, 27-31 Oct 2016 http://meta2016.sciencesconf.org ********************************** Prof. E-G. Talbi Univ. Lille, CNRS, INRIA -- ********************************** META'2016 Marrakech, 27-31 Oct 2016 http://meta2016.sciencesconf.org ********************************** Prof. E-G. Talbi Univ. Lille, CNRS, INRIA

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'STATS COURSE - Spatial Analysis of Multivariate Ecological Data Using R - PIERRE LEGENDRE'
by Oliver Hooker 05 May '16

05 May '16

“Advances in Spatial Analysis of Multivariate Ecological Data: Theory and Practice” http://prstatistics.com/course/advances-in-spatial-analysis-of-multivariate… This course is being delivered by Prof. Pierre Legendre who is a leading expert in numerical ecology and author of the book titled ‘Numerical ecology’ This course will run from 11th – 15th July 2016 at SCENE Field Station, Loch Lomond national park, Scotland. The course will describe recent methods (concepts and R tools) that can be used to analyse spatial patterns in community ecology. The umbrella concept of the course is beta diversity, which is the spatial variation of communities. These methods are applicable to all types of communities (bacteria, plants, animals) sampled along transects, regular grids or irregularly distributed sites. The new methods, collectively referred to as spatial eigen-function analysis, are grounded into techniques commonly used by community ecologists, which will be described first: simple ordination (PCA, CA, PCoA), multivariate regression and canonical analysis, permutation tests. The choice of dissimilarities that are appropriate for community composition data will also be discussed. The focal question is to determine how much of the community variation (beta diversity) is due to environmental sorting and to community-based processes, including neutral processes. Recently developed methods to partition beta diversity in different ways will be presented. Extensions will be made to temporal and space-time data. Course content is as follows Day 1 • Introduction to data analysis. • Ordination in reduced space: principal component analysis (PCA), correspondence analysis (CA), principal coordinate analysis (PCoA). • Transformation of species abundance data tables prior to linear analyses. Day 2 • Measures of similarity and distance, especially for community composition data. • Multiple linear regression. R-square, adjusted R-square, AIC, tests of significance. • Polynomial regression. • Partial regression and variation partitioning. Day 3 • Statistical testing by permutation. • Canonical redundancy analysis (RDA) and canonical correspondence analysis (CCA). Multivariate analysis of variance by canonical analysis. • Forward selection of environmental variables in RDA. Day 4 • Origin of spatial structures. • Beta diversity partitioning and LCBD indices • Replacement and richness difference components of beta diversity. Day 5 • Spatial modelling: Multi-scale modelling of the spatial structure of ecological communities: dbMEM, generalized MEM, and AEM methods. • Community surveys through space and time: testing the space-time interaction in repeated surveys. • Additional module depending on time – Is the Mantel test useful for spatial analysis in ecology and genetics? Please email any inquiries to oliverhooker(a)prstatistics.com or visit our website www.prstatistics.com or to book online http://prstatistics.com/course/advances-in-spatial-analysis-of-multivariate… Please feel free to distribute this material anywhere you feel is suitable Upcoming courses - email for details oliverhooker(a)prstatistics.com SPATIAL ANALYSIS OF ECOLOGIC AL DATA USING R (April) ADVACNING IN STATISTICAL MODELLING USING R (May) TIMES SERIES DATA ANALYSIS FOR ECOLOGISTS AND CLIMATOLOGISTS (May) INTRODUCTION TO PYTHON FOR BIOLOGISTS (May) ADVANCES IN DNA TAXONOMY USING R (August) GENETIC DATA ANALYSIS USING R (August) INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (August) MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R (October) LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (October) APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS (October) Dates still to be confirmed - email for details oliverhooker(a)prstatistics.com STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R INTRODUCTION TO R AND STATISTICS FOR BIOLOGISTS PHYLOGENETIC DATA ANALYSIS USING R BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS Oliver Hooker PR Statistics 3/1 128 Brunswick Street Glasgow G1 1TF +44 (0) 7966500340 www.prstatistics.com www.prstatistics.com/organiser/oliver-hooker/

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Edinburgh Genomics - MinION and Python workshops
by Bert Overduin 04 May '16

04 May '16

Dear all, We still have a few places available on our workshop "Oxford Nanopore MinION Sequencing - Data Handling, Analysis and Applications" on Monday 13 June 2016. This 1-day workshop will focus on the handling, analysis and applications of MinION sequence data. The workshop will be a combination of presentations, demos and hands-on tutorials. In the hands-on tutorials a wide range of software programs will be used, some of which were especially developed for the MinION. The workshop is aimed at anyone who is working with, or is planning to work with, Oxford Nanopore MinION sequence data. Note that we are also offering three(!) different weeklong Python courses, an introductory one, an advanced one, as well as one focused on data manipulation and visualisation. All three are taught by dr Martin Jones, founder of Python for Biologists (http://pythonforbiologists.com) and author of several books on Python ( http://pythonforbiologists.com/index.php/books/) Registration for all workshops can be done through the workshop pages indicated below, on which you can also find much more detailed information about each workshop. Please don't hesitate to contact me if you have a question with regard to any of the workshops. I hope to see you at one (or more) of our workshops! With kind regards, Bert Overduin ************************* *1-day Oxford Nanopore MinION Sequencing - Data Handling, Analysis and Applications* Date: Mon 13 June 2016 Price: £155 Registration: participant selection Deadline: Mon 16 May 2016 noon Details: https://genomics.ed.ac.uk/oxford-nanopore-minion-sequencing-data-handling-a… *"I liked this course - it's a good, well-rounded primer for this subject area." (Feb 2016)* ************************* *5-day Introduction to Python for Biologists* Date: Mon 11- Fri 15 July 2016 Price: £500 Registration: first come first serve Deadline: Mon 13 June 2016 noon Details: https://genomics.ed.ac.uk/introduction-python-biologists-july-2016 *"Great learning from someone with a biology background rather than computer science - meant we were on the same wavelength. The course really was excellent!" (Feb 2016)* *"This is the best course I have ever taken - well paced, excellent teaching, and the feeling at the end that I had learnt skills I could apply to my research." (Apr 2016)* ************************* *5-day Advanced Python for Biologists* Date: Mon 25 - Fri 29 July 2016 Price: £500 Registration: first come first serve Deadline: Mon 27 June 2016 noon Details: https://genomics.ed.ac.uk/advanced-python-biologists-july-2016 *"It was just what I needed to start writing more complex code." (Aug 2015)* ************************* *5-day Data Manipulation and Visualisation with Python* Date: Mon 5 - Fri 9 September 2016 Price: £500 Registration: first come first serve Deadline: Mon 8 August 2016 noon Details: https://genomics.ed.ac.uk/data-manipulation-and-visualization-python ************************* -- Bert Overduin, PhD TRAINING AND OUTREACH BIOINFORMATICIAN Bert.Overduin(a)ed.ac.uk orcid.org/0000-0002-5281-8838 EDINBURGH GENOMICS The University of Edinburgh Ashworth Laboratories The King's Buildings Charlotte Auerbach Road Edinburgh EH9 3FL Scotland, United Kingdom tel. +44(0)1316507403 http://genomics.ed.ac.uk The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.

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Network Inference workshop at ECCB2016: abstract submission deadline extended on May 22nd
by Eric Bonnet 04 May '16

04 May '16

We are glad to announce the ECCB 2016 workshop: Network Inference : New Methods and Data EXTENDED ABSTRACT SUBMISSION DEADLINE: May 22nd http://www.eccb2016.org/programme/workshops/w2/ Scope This one day session (SIG) will bring together experts from computational biology and machine learning to present recent advances in the development and application of gene regulatory network inference methods, as well as novel emerging data types (such as single-cell, epigenomics ...) suitable for network inference. The SIG will be split into two half day sessions. The first half will focus entirely on novel network inference methods, while the second half will focus on opportunities and challenges arising from new data types. Each session will feature an invited speaker and three short talks. Registration https://easychair.org/conferences/?conf=ninf2016 Venue The workshop will take place in the World Forum Convention Centre of Hague, The Netherlands on September 4th 2016 as part of the 15th European Conference on Computational Biology (ECCB 2016). Topics Network Inference Machine learning Biological networks Biological data types NGS Applications of biological network inference Audience The workshop is suitable for wide audience as computational biologists interested in networks inference, computational and experimental biologists, clinicians, plant biologists and anyone who is interested to be exposed to the latest trends and applications of network biology inference from various types of biological data. Organizing Committee: Dr. Anagha Joshi, Roslin Institute, University of Edinburgh, UK. Dr. Tom Michoel, Roslin Institute, University of Edinburgh, UK. Dr. Eric Bonnet, Centre National de Génotypage, CEA, Paris, France.

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System administrator for ELIXIR Node in Luxembourg
by Venkata Pardhasaradhi SATAGOPAM 03 May '16

03 May '16

Dear all The Luxembourg Centre for Systems Biomedicine (LCSB) at the University of Luxembourg is seeking an enthusiastic team member for the following position: System administrator for ELIXIR Node in Luxembourg (m/f) * Initial contract duration : 3 years, 40h/week, extension possible * Employee status (start date: as soon as possible) * Ref. : S-STR-4029-00-B The Luxembourg Centre for Systems Biomedicine (LCSB) is an interdisciplinary research centre at the University of Luxembourg. LCSB develops and applies systems-level approaches to gain insight into the molecular and cellular mechanisms of human diseases. Experimental and computational approaches are combined to analyse the complexity of biological systems underlying disease pathogenesis. The LCSB is pioneering the way for a predictive, preventive and personalised medicine. LCSB is currently establishing the ELIXIR (the European life-sciences Infrastructure for biological Information www.elixir-europe.org<http://www.elixir-europe.org>) national node of Luxembourg focusing on “Clinical and Translational Medicine Research Informatics”. We are looking for a System administrator for the prospective ELIXIR Node. The job owner will help to provide a secure, scalable and highly available Virtual Private Cloud (VPC) & IT environment adequate to the needs of the ELIXIR services and user community, through proactive monitoring and support of the heterogeneous hardware and software components. One important task will include the support of the whole scientific software landscape but will also include the further development and refinement of existing and upcoming software analysis pipelines. The job owner should be able to perform and lead data management / processing tasks. Your Role Duties of the position include, but are not limited to: * Perform daily duties as regards VPC configuration management, on as-needed basis * Build Inventory of VPC Equipment; Hardware, Software, Services and redundancy Procedures * Maintain and monitor support information in Ticketing System(s) and related tools * Provide system and network administration and support firewalls, network organisation, and be able to handle storage services, including fileserver-client issues * Write and maintain documentation for technical procedures, on as needed basis * Improve on procedures/practices, as advancements in the field dictate * Become the primary administrator for outsourced services/accounts (e.g. web hosting) and assist in the procurement of in-house services via external vendors, if/when so desired * Assist with system backup and recovery services and system administration tools and processes, e.g. user administration, networking, file servers; familiarity with the LAMP stack, TCP/IP networking and supporting them in tandem * Provide support for bioinformatics tools and software pipelines and be involved in their further development and refinement * Be responsible to lead bioinformatics related data analysis tasks Your Profile * Degree in computer science or bioinformatics or related fields. * Strong system administration and hardware experience including full stack up to OS virtualization is required (OpenStack / oVirt knowledge will be considered an asset). * Good computer programming experience (Python, linux scripting) * Experience with Puppet, Ansible or Chef will be considered an asset * Knowledge of modern web development technologies will be considered an asset * Excellent communication skills and the ability to articulate clearly the scientific and technical needs and to work within an interdisciplinary setting, communicating with other internal/external partners. We offer * A fully funded position with a very competitive salary. * Participate in the building of state-of-the-art translational medicine platform to support clinical projects from national, EU and beyond. * An opportunity to join the fast-growing Bioinformatics Core Facility group headed by Dr. Reinhard Schneider in the newly created LCSB. * An exciting international environment. The University is an equal opportunity employer. Further Information For questions, please contact Venkata Satagopam (venkata.satagopam(a)uni.lu<mailto:venkata.satagopam@uni.lu>). Applications (in English) should contain the following documents: * A detailed curriculum vitae * Cover letter mentioning the reference number * List of publications/infrastructure and software projects * Description of past experience and future interests * Name and addresses of three referees Please apply online until 10th June 2016. URL: http://emea3.mrted.ly/11opj -- Venkata P. Satagopam Bioinformatics Core Luxembourg Centre For Systems Biomedicine (LCSB) University of Luxembourg Campus Belval, House of Biomedicine II 6, avenue du Swing L-4367 Belvaux T +352-466-644-6421 F +352-466-644-6949 venkata.satagopam(a)uni.lu<mailto:venkata.satagopam@uni.lu> http://lcsb.uni.lu ----- This message is confidential and may contain privileged information. It is intended for the named recipient only. If you receive it in error please notify me and permanently delete the original message and any copies. -----

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BIOKDD 2016 Call for Papers
by Laukens Kris 03 May '16

03 May '16

****CALL FOR PAPERS****** 15th International Workshop on Data Mining in Bioinformatics (BIOKDD'16) August 14 2016 San Francisco, USA http://home.biokdd.org/biokdd16/ http://www.facebook.com/Biokdd The goal of the 16th International Workshop on Data Mining in Bioinformatics (BIOKDD'16) is to encourage KDD researchers to tackle the numerous challenges of mining and learning in Bioinformatics, Biomedical and Health Informatics. Thus this year, the workshop will feature the theme of “Latest Advances of Mining and Learning in Bioinformatics, Biomedical and Health Informatics”. This field focuses on the use of data mining and machine learning approaches for the analysis of the large amount of heterogeneous complex biological and medical data being generated together with innovative applications in biomedical and health informatics. The key goal is thus to build accurate predictive or descriptive models from data enabling either novel discoveries in basic biology and medicine or an effective use of the latest advances of data mining in healthcare. We encourage papers that propose novel data mining techniques for areas including but not limited to * Predictive modeling for complex phenotypes from large-scale biological data * Discovery of biological networks and pathways underlying biological processes and diseases * Processing of new/next-generation sequencing (NGS) data * Discovery of genotype-phenotype associations * Biomarker discovery in clinical and genomic data * Data analytics for clinical informatics * Data integration for biomedical applications * Comparative genomics * Metagenome analysis using sequencing data * RNA-seq and microarray-based gene expression analysis * Genome-wide analysis of non-coding RNAs * Genome-wide regulatory motif discovery * Structural bioinformatics * Correlating NGS with proteomics data analysis * Functional annotation of genes and proteins * Cheminformatics * Special biological data management techniques * Information visualization and Visual analytics for biomedical data * Predictive modeling for personalized treatment * Semantic web and ontology in Biomedicine * Privacy and security issues in genomics and healthcare * Text mining for biomedical literature and clinical notes * Information retrieval for healthcare and Biomedical applications * Biomedical signal analysis and processing * Intelligent medical data management * Collaboration technologies for biomedicine * Social networks for biomedicine **Important Dates** May 27th, 2016 Deadline for Submission of Papers June 13th, 2016 Notification of Acceptance; Workshop Registration Open June 30th, 2016 Submission of Camera-ready Papers August 14th, 2016 Workshop Presentation All deadlines are at 11:59 PM Pacific Standard Time. **Submissions** Papers should be at most 10 pages long, single-spaced, in font size 10 or larger with one-inch margins on all sides. Using the ACM Proceedings Format is highly recommended. Paper should be submitted in PDF format through EasyChair at the following link: https://easychair.org/conferences/?conf=biokdd2016 Papers will be published in the webpage. A selection of accepted papers will also be invited to be submitted to a special issue of the reputed IEEE Transactions on Computational Biology and Bioinformatics. **Workshop Organizers** Program Chairs: Sara C. Madeira, Instituto Superior Técnico, <sara.madeira(a)tecnico.ulisboa.pt> Chandan K. Reddy, Wayne State University, USA <reddy(a)cs.wayne.edu> General Chairs: Mohammed J. Zaki, Rensselaer Polytechnic Institute, <zaki(a)cs.rpi.edu> Jake Y. Chen, Indiana University - Purdue University Indianapolis, <jakechen(a)iupui.edu>

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