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Welcome to ß-Lactamase
Beta-lactamases are enzymes  produced by some bacteria and are responsible for their resistance to beta-lactam antibiotics like penicillins, cephamycins, and carbapenems (ertapenem) (Cephalosporins are relatively resistant to beta-lactamase). These antibiotics have a common element in their molecular structure: a four-atom ring known as a beta-lactam.








Responsibilities:

Developing, implementing, and performing state-of-the-art bioinformatics analyses, applications, and workflows to grow our translational genomics and bioinformatics capabilities and infrastructure.


Qualifications:

  • M.S. in Bioinformatics or related discipline, with 1-3 years of experience required;
  • Ph.D. in Bioinformatics or related discipline, with 3-5 years of experience preferred;
  • Strong background in software development on Linux system;
  • High programming proficiency in Java, Perl, or Python;
  • Solid experience in next generation sequencing data analysis;
  • Demonstrate initiative in experimenting with new technologies;
  • Ability to address business needs with effective and efficient technical solutions;
  • Cooperate with team members and clients from a broad range of disciplines and subject level expertise;
  • Able to work independently and collaboratively in a dynamic work environment;
  • Strong communication skills, both written and verbal.










In the last ten years, the open source R statistics language has exploded in popularity and functionality, emerging as the data scientist's tool of choice. Today, R is used by over 2 million analysts worldwide, many having been introduced to its elegance and power in academia. Users around the world have embraced R to solve their most challenging problems in fields ranging from computational biology to quantitative finance, and to train their students in these same fields. The result has been an explosion of R analysts and applications, leading to enthusiastic adoption by premier analytics-driven companies like Google, Facebook, and and the New York Times.

















Center for non-coding RNA in Technology and Health (RTH), http://rth.dk, address non-coding RNAs in (inflammatory) diseases through a multi-disciplinary research approach spanning bioinformatics, high-throughput data, molecular biology and genetics. The center has an open PhD position in Bioinformatics and we are looking for a person to join our team from September, or soon thereafter. The position is for three years.
Background 
Non-coding RNAs (ncRNAs) have been established as a highly abundant class of genes which play numerous important roles in the cell and in disease. These ncRNAs often contain RNA structure either for the entire sequence or sometimes as minor "domains". In RTH we have developed a range of computational tools for the analysis of both structured RNAs and high-throughput data.

Job description 
Within RTH material has been collected for a range of diseases and will be combined with in silico generated information of structured RNA and a range of information such as expression and (protein and RNA) binding generated from predictions and experiments. A key goal of the project is to filter and rank selected candidates for detailed molecular functional analysis with respect to the disease samples. Pipelines for expression analysis, data integration and statistical analysis will be developed within the project.

Qualification requirements 
The applicant should hold professional as well as personal skills and qualifications as stated below:

  • A master degree in bioinformatics, computational biology, computer science or similar.
  • Very strong experience with script languages such as Perl or Python (or similar).
  • Strong experience with the linux/unix environment, command lines and shell scripting.
  • Experience with statistical analysis.
  • Differential expression analysis (with background correction / multiple testing).
  • Possess good interpersonal skills.
  • Be excellent in English, writing and speech.
In addition to the above, weight will be given to applicants meeting one or more of the following requirements:
  • General knowledge about RNA structure folding algorithms.
  • C or C++.
Terms of employment 
The PhD fellowships are to be completed in accordance with the Ministerial order on the PhD programme at the universities (PhD order) the Ministry of Science, Technology and Innovation and the Regulations and guidelines for the conferment of the PhD degree by the Faculty. The terms of employment are stated in the agreement between The Danish Confederation of Professional Associations and the Ministry of Finance. The basic annual salary for PhD students starts at DKK 300.000 (approx. Euro 40.500). In addition, the successful candidate will enter a pension fund scheme as well as paid holidays after one year. Operating costs such as course fees, project expenses, travel and stays abroad, etc. are subsidized by the project.

Place of employment 
RTH is mainly located on the Frederiksberg campus, close to the center of Copenhagen. We are an interdisciplinary center with national as well as international collaborators and visits to the partners are organized when necessary. Our research environment is highly international and stimulating. We frequently organize seminars, workshops, PhD summer schools with international speakers and have retreats with our international collaborators.

Application procedure 
Apply by clicking "Apply online" below. Applications - in English - must include:

  • Cover Letter applying including your motivation, background and why your skills match the requirements. Max 1 page.
  • CV incl. education, research experience, programming skills and other skills relevant for the position.
  • Diploma and transcripts of records (B.Sc. and M.Sc.). If the M.Sc. degree is from a foreign university, it must be documented that it is on a level equivalent with a Danish M.Sc.
  • Other information for consideration, e.g. list of publications (if any).
  • Personal Recommendations.
  • A maximum of 3 relevant scientific works (e.g. peer reviewed papers) which the applicant wishes to be included in the assessment.
  • If the applicant has another nationality than Danish and does not have English/
American as native language, a TOEFL(+TSE) (minimum score 560 pts. (paper based) or 83 pts. (internet based)) or IELTS (minimum score 6.0 pts.) official certificate is mandatory. If you have not passed this at the time of application, you must include documentation that you have signed up for the test including a statement of the expected date for result.
Application deadline 
The applications must be received latest by Sunday, September 8th, 2013.

Application received after the closing time will not be considered.
Questions 
For further information about the

  • scientific content, please contact: Professor Jan Gorodkin, e-mail: gorodkin@rth.dk, phone +45 353 34704, +45 353 33578 (direct).
  • application procedure and formalities, please contact: Administrative Officer, Marie-Louise Rosenlund, e-mail: mln@sund.ku.dk, phone: +45 353 32898.
Deadline: 2013-09-08
Employer: Faculty of Health Sciences, University of Copenhagen.
Founded in 1479, the University of Copenhagen is the oldest university in Denmark. With 37,000 students and 9,000 employees, it is among the largest universities in Scandinavia and one of the highest ranking in Europe. The University consists of six faculties, which cover Health and Medical Sciences, Humanities, Law, Science, Social Sciences and Theology. 
Frist: 08-09-2013 

Arbejdsgiver: Det Sundhedsvidenskabelige Fakultet

















Bioconductor is an open source, open development software project to provide tools for the analysis and comprehension of high-throughput genomic data. It is based primarily on the R programming language.
The Bioconductor release version is updated twice each year, and is appropriate for most users. There is also a development version, to which new features and packages are added prior to incorporation in the release. A large number of meta-data packages provide pathway, organism, microarray and other annotations.
The Bioconductor project started in 2001 and is overseen by a core team, based primarily at the Fred Hutchinson Cancer Research Center, and by other members coming from US and international institutions. It gained widespread exposure in a 2004 Genome Biology paper.
Bioconductor Packages

Most Bioconductor components are distributed as R packages. The functional scope of Bioconductor packages includes the analysis of DNA microarray, sequence, flow, SNP, and other data.
Project Goals
The broad goals of the Bioconductor project are:
  • To provide widespread access to a broad range of powerful statistical and graphical methods for the analysis of genomic data.
  • To facilitate the inclusion of biological metadata in the analysis of genomic data, e.g. literature data from PubMed, annotation data from Entrez genes.
  • To provide a common software platform that enables the rapid development and deployment of extensible, scalable, and interoperable software.
  • To further scientific understanding by producing high-quality documentation and reproducible research.
  • To train researchers on computational and statistical methods for the analysis of genomic data.

Main Project Features

The R Project for Statistical Computing. Using R provides a broad range of advantages to the Bioconductor project, including:
  • A high-level interpreted language to easily and quickly prototype new computational methods.
  • A well established system for packaging together software with documentation.
  • An object-oriented framework for addressing the diversity and complexity of computational biology and bioinformatics problems.
  • Access to on-line computational biology and bioinformatics data.
  • Support for rich statistical simulation and modeling activities.
  • Cutting edge data and model visualization capabilities.
  • Active development by a dedicated team of researchers with a strong commitment to good documentation and software design.
Read more














  • Workshops:


Cold Spring Harbor Courses: meetings.cshl.edu/courses.html

Cold Spring Harbor has been offering advanced workshops and short courses in the life sciences for years. Relevant workshops include Advanced Sequencing Technologies & Applications, Computational & Comparative Genomics, Programming for Biology, Statistical Methods for Functional Genomics, the Genome Access Course, and others. Unlike most of the others below, you won't find material from past years' CSHL courses available online.

Canadian Bioinformatics Workshops: bioinformatics.ca/workshops
Bioinformatics.ca through its Canadian Bioinformatics Workshops (CBW) series began offering one and two week short courses in bioinformatics, genomics and proteomics in 1999. The more recent workshops focus on training researchers using advanced high-throughput technologies on the latest approaches being used in computational biology to deal with the new data. Course material from past workshops is freely available online, including both audio/video lectures and slideshows. Topics include microarray analysis, RNA-seq analysis, genome rearrangements, copy number alteration,network/pathway analysis, genome visualization, gene function prediction, functional annotation, data analysis using R, statistics for metabolomics, and much more.

UC Davis Bioinformatics Training
The UC Davis Bioinformatics Training program offers several intensive short bootcamp workshops on RNA-seq, data analysis and visualization, and cloud computing with a focus on Amazon's computing resources. They also offer a week-long Bioinformatics Short Course, covering in-depth the practical theory and application of cutting-edge next-generation sequencing techniques. Every course's documentation is freely available online, even if you didn't take the course.

This intensive two week summer course will introduce attendees with a strong biology background to the practice of analyzing short-read sequencing data from Illumina and other next-gen platforms. The first week will introduce students to computational thinking and large-scale data analysis on UNIX platforms. The second week will focus on mapping, assembly, and analysis of short-read data for resequencing, ChIP-seq, and RNAseq. Materials from previous courses are freely available online under a CC-by-SA license.

Genetic Analysis of Complex Human Diseases: hihg.med.miami.edu/edu...
The Genetic Analysis of Complex Human Diseases is a comprehensive four-day course directed toward physician-scientists and other medical researchers. The course will introduce state-of-the-art approaches for the mapping and characterization of human inherited disorders with an emphasis on the mapping of genes involved in common and genetically complex disease phenotypes. The primary goal of this course is to provide participants with an overview of approaches to identifying genes involved in complex human diseases. At the end of the course, participants should be able to identify the key components of a study team, and communicate effectively with specialists in various areas to design and execute a study. The course is in Miami Beach, FL. (Full Disclosure: I teach a section in this course.) Most of the course material from previous years is not available online, but my RNA-seq & methylation lectures are on Figshare.

UAB Short Course on Statistical Genetics and Genomics:soph.uab.edu/ssg/...
Focusing on the state-of-art methodology to analyze complex traits, this five-day course will offer an interactive program to enhance researchers' ability to understand & use statistical genetic methods, as well as implement & interpret sophisticated genetic analyses. Topics include GWAS Design/Analysis/Imputation/Interpretation; Non-Mendelian Disorders Analysis; Pharmacogenetics/Pharmacogenomics; ELSI; Rare Variants & Exome Sequencing; Whole Genome Prediction; Analysis of DNA Methylation Microarray Data; Variant Calling from NGS Data; RNAseq: Experimental Design and Data Analysis; Analysis of ChIP-seq Data; Statistical Methods for NGS Data; Discovering new drugs & diagnostics from 300 billion points of data. Video recording from the 2012 course are available online.

MBL Molecular Evolution Workshop: hermes.mbl.edu/education/...
One of the longest-running courses listed here (est. 1988), the Workshop on Molecular Evolution at Woods Hole presents a series of lectures, discussions, and bioinformatic exercises that span contemporary topics in molecular evolution. The course addresses phylogenetic analysis, population genetics, database and sequence matching, molecular evolution and development, and comparative genomics, using software packages including AWTY, BEAST, BEST, Clustal W/X, FASTA, FigTree, GARLI, MIGRATE, LAMARC, MAFFT, MP-EST, MrBayes, PAML, PAUP*, PHYLIP, STEM, STEM-hy, and SeaView. Some of the course materials can be found by digging around the course wiki.


  • Online Material:


Canadian Bioinformatics Workshops: bioinformatics.ca/workshops
(In person workshop described above). Course material from past workshops is freely available online, including both audio/video lectures and slideshows. Topics include microarray analysis, RNA-seq analysis, genome rearrangements, copy number alteration, network/pathway analysis, genome visualization, gene function prediction, functional annotation, data analysis using R, statistics for metabolomics, andmuch more.

UC Davis Bioinformatics Training Program:
(In person workshop described above). Every course's documentation is freely available online, even if you didn't take the course. Past topics include Galaxy, Bioinformatics for NGS, cloud computing, and RNA-seq.

(In person workshop described above). Materials from previous courses are freely available online under a CC-by-SA license, which cover mapping, assembly, and analysis of short-read data for resequencing, ChIP-seq, and RNAseq.

EMBL-EBI Train Online: www.ebi.ac.uk/training/online
Train online provides free courses on Europe's most widely used data resources, created by experts at EMBL-EBI and collaborating institutes. Topics include Genes and Genomes, Gene Expression,Interactions, Pathways, and Networks, and others. Of particular interest may be the Practical Course on Analysis of High-Throughput Sequencing Data, which covers Bioconductor packages for short read analysis, ChIP-Seq, RNA-seq, and allele-specific expression & eQTLs.

UC Riverside Bioinformatics Manuals: manuals.bioinformatics.ucr.edu
This is an excellent collection of manuals and code snippets. Topics include Programming in R, R+Bioconductor, Sequence Analysis with R and Bioconductor, NGS analysis with Galaxy and IGV, basicLinux skills, and others.

Software Carpentry: software-carpentry.org
Software Carpentry helps researchers be more productive by teaching them basic computing skills. We recently ran a 2-day Software Carpentry Bootcamp here at UVA. Check out the online lectures for some introductory material on Unix, Python, Version Control, Databases, Automation, and many other topics.

Coursera: coursera.org/courses
Coursera partners with top universities to offer courses online for anytone to take, for free. Courses are usually 4-6 weeks, and consist of video lectures, quizzes, assignments, and exams. Joining a course gives you access to the course's forum where you can interact with the instructor and other participants. Relevant courses include Data Analysis, Computing for Data Analysis using R, and Bioinformatics Algorithms, among others. You can also view all of Jeff Leek's Data Analysis lectures on Youtube.
Quite different from the others listed here, Rosalind is a platform for learning bioinformatics through gaming-like problem solving. Visit the Python Village to learn the basics of Python. Arm yourself at theBioinformatics Armory, equipping yourself with existing ready-to-use bioinformatics software tools. Or storm the Bioinformatics Stronghold, implementing your own algorithms for computational mass spectrometry, alignment, dynamic programming, genome assembly, genome rearrangements, phylogeny, probability, string algorithms and others.


  • Other Resources:


Titus Brown's list bioinformaticscourses: Includes a few others not listed here (also see the comments).
GMOD Training and Outreach: GMOD is the Generic Model Organism Database project, a collection of open source software tools for creating and managing genome-scale biological databases. This page links out to tutorials on GMOD Components such as Apollo, BioMart, Galaxy, GBrowse, MAKER, and others.
Seqanswers.com: A discussion forum for anything related to Bioinformatics, including Q&A, paper discussions, new software announcements, protocols, and more.
Biostars.org: Similar to SEQanswers, but more strictly a Q&A site.
BioConductor Mailing list: A very active mailing list for getting help with Bioconductor packages. Make sure you do some Google searching yourself first before posting to this list.
Bioconductor Events: List of upcoming and prior Bioconductor training and events worldwide.
Learn Galaxy: Screencasts and tutorials for learning to use Galaxy.
Galaxy Event Horizon: Worldwide Galaxy-related events (workshops, training, user meetings) are listed here.
Galaxy RNA-Seq Exercise: Run through a small RNA-seq study from start to finish using Galaxy.
Rafael Irizarry's Youtube Channel: Several statistics and bioinformatics video lectures.
PLoS Comp Bio Online Bioinformatics Curriculum: A perspective paper by David B Searls outlining a series of free online learning initiatives for beginning to advanced training in biology, biochemistry, genetics, computational biology, genomics, math, statistics, computer science, programming, web development, databases, parallel computing, image processing, AI, NLP, and more.

Getting Genetics Done: Shameless plug – I write a blog highlighting literature of interest, new tools, and occasionally tutorials in genetics, statistics, and bioinformatics. I recently wrote this post about how to stay current in bioinformatics & genomics.















Why Use Consed?

  1. Supports Illumina, 454, other Next-Gen and Sanger Reads and allows mixtures of these read types
  2. Consed now includes BamScape which can view bam files with unlimited numbers of reads. BamScape can bring up consed to edit reads and the reference sequence in targetted regions.
  3. Consed is compatible with Newbler, Cross_match, Phrap, MIRA, Velvet and PCAP output.
  4. Quickly takes the user to each variant site for viewing (also available as an automated report)
  5. Overview of assembly can help detect and fix misassemblies
  6. Consed is licensed to over 4000 sites and climbing. In *active* use at over 230 sites in 36 countries including biotech, chemical, pharmaceutical, and agricultural companies, major genome centers, small academic labs, and government labs
  7. Editing time reduced by the program's ability to pin-point problem areas
  8. Editing is guided by error probabilities
  9. Consed is able to pick primers very successfully (98 out of 98 in a controlled study). Labs that use it are quite happy with it.
  10. Able to pick PCR primers to amplify a region, even if you only have a fasta file for the region