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    June 18-19, 2020
    Florence, Italy


    The objective of the Conference is to promote transnational cooperation and share good practice in the field of education. The Conference is also an excellent opportunity for the presentation of previous and current education projects and initiatives.


    The Call for Papers is addressed to teachers, researchers and experts in the field of education as well as to coordinators of teaching and training projects. Experts in the field of education are therefore invited to submit an abstract of a paper to be presented in the conference.

    There will be three presentation modalities: oral, poster and virtual presentations.

    All accepted papers will be included in the Conference Proceedings published by Filodiritto Editore with ISBN, ISSN, DOI and ISPN codes. This publication will be sent to be reviewed for inclusion in Conference Proceedings Citation Index by Thomson Reuters (ISI-Clarivate). The publication will also be included in and indexed in Google Scholar.

    For further information, please contact us at the following address: foe[at] or visit the Future of Education conference website.


    Deadline for submitting Abstracts: February 27, 2020
    Notification of Acceptance / Rejection for Abstracts: March 12, 2020
    Deadline for final submission of Papers: April 24, 2020
    Conference days: June 18-19, 2020


    October 23 - 25, 2019
    Munich, Germany[...]ction

    Advance your research. Understand NGS and analyze sequenced data yourself.


    • Learn the essential computing skills for NGS bioinformatics
    • Understand NGS technology, algorithms and data formats
    • Use bioinformatics tools for handling sequencing data
    • Perform first downstream analyses for studying genetic variation


    The purpose of this workshop is to get a deeper understanding in Next-Generation Sequencing (NGS) with a special focus on bioinformatics issues. Advantages and disadvantages of current sequencing technologies and their implications on data analysis will be discovered. The participants will be trained on understanding their own NGS data, finding potential problems/errors therein and finally perform their first downstream analysis (variant calling). In the course we will use a real-life NGS dataset from the current market leader Illumina.

    All workshop attendees will be enabled to perform important first tasks of NGS data analysis themselves. The course layout has been adapted to the needs of beginners in the field of NGS bioinformatics and allows scientists with no or little background in computer science to get a first hands-on experience in this new and fast evolving research topic.

    More information is on the website.
    Events: CfP: Applied Bioinformatics in Life Sciences (3rd edition)
    Submitted by Rob van Ham; posted on Monday, September 23, 2019

    February 13-14, 2020
    Leuven, Belgium[...]ition


    Bioinformatics has quickly become an integral part of life sciences research by enabling innovative computational approaches in an increasingly data-dense environment.

    Inspired by the sold-out editions in 2016 and 2018, VIB (a non-profit life sciences research institute) is organizing this third edition to highlight recent developments in bioinformatics research, and to showcase its impact in medical, agricultural, and biotechnological research.

    Nationally and internationally renowned speakers will present recent scientific findings in applied bioinformatics. They will shed light on the future perspectives of their research in the following plenary sessions:
    • Microbial & plant genomics: from simple to complex
    • Structural bioinformatics and proteomics
    • Data integration, machine learning and networks
    • Single cell bioinformatics
    Besides an inspiring scientific program, conference participants will have ample networking opportunities during poster sessions and the conference dinner.


    We offer 5 travel grants to international attendees, which will reimburse travel costs up to 400 Euros. Are you interested in attending ABLS20 and want to have a chance on a travel grant? Submit your motivation below by clicking on the 'Apply for a grant' button before 15 November. The organizing committee will notify you of your travel grant acceptance on 22 November 2019. No registration is needed before submitting a travel grant proposal. When you're awarded with a travel grant you will receive a practical email containing the next steps. Note that being awarded a travel grant does not mean being registered for the conference. Scroll down to apply for your grant.


    Roser Vento, Sanger Institute, UK
    Klaus Mayer, Helmholtz Zentrum München, DE
    Thijs Ettema, Wageningen University, NL
    Rohit Pappu, Washington University, US
    Patrick Aloy, Structural Bioinformatics Lab, IRB Barcelona, ES
    Helen Parkinson, EMBL-EBI, UK
    Nick Loman, University of Birmingham, UK
    Daifeng Wang, Stony Brook University, US
    Aedin Culhane, Dana-Farber Cancer Institute & Harvard TH Chan School of Public Health, US
    Sushmita Roy, Dept. of Biostatistics and Medical Informatics, Wisconsin Institute for Discovery, University of Wisconsin, US
    Olga Vitek, Northeastern University, US
    Nikolai Slavov, Northeastern University, US
    Evangelia Petsalaki, EMBL-EBI, UK
    Ashley Lu, VIB-KU Leuven Center for Brain & Disease Research, BE
    Sofia Forslund, Experimental and Clinical Research Centre (ECRC, a joint venture of the Max Delbrück Center for Molecular Medicine and the Charité University Hospital), DE
    Laurent Gatto, De Duve Institute – UC Louvain, BE
    Erik Garrison, UC Santa Cruz, US


    Travel grants deadline: November 15, 2019
    Abstract deadline: December 2, 2019
    Early bird deadline: December 20, 2019
    Final registration: January 13, 2020

    fCite is a fractional citation tool to quantify an individual's research output. Divide citations and RCR metrics by the number of the authors. The metrics are calculated based on PUBMED (17M publications) and ORCID (600k profiles).



    More in bioRXiv preprint:

    March 1-4, 2020
    Moscone South Convention Center
    San Francisco, CA

    BIO-IT WORLD WEST: Driving Scientific Discoveries with Data, Infrastructure, and Technology Tools to Improve Patient Health and Guide Precision Medicine

    Bio-IT World WEST is excited to return to the Molecular Med TRI-CON in 2020 with an expanded educational and networking program that promises to build on the success of our Boston-based 19th Annual Bio-IT World Conference & Expo. For the past 19 years, Bio-IT World Conference & Expo has established itself as a premier event focused on the innovative IT and informatics applications and enabling technologies that are driving the future of precision medicine. Bio-IT World Conference & Expo highlights the new frontiers in drug discovery & development, biomedical research, and clinical and healthcare initiatives made possible by these cutting-edge technologies. Join us at Bio-IT World WEST with an entirely new audience as we explore:
    • Digitization of Pharma R&D
    • AI-Enabled Drug Discovery and Development
    • Emerging Technologies for Life Sciences
    • Software Tools, Services, and Applications
    Early registration discounts are available until November 1.

    View more details and register at
    Education: Training in Rosetta for Molecular Modeling and Design @NIH
    Submitted by Vijayaraj Nagarajan; posted on Wednesday, September 18, 2019

    October 28-30, 2019
    National Institutes of Health
    9000 Rockville Pike
    Building 60, Room 162
    Bethesda, MD 20892, USA


    Participants will get a brief introduction to basic linux commands, a short presentation on the capabilities of Rosetta, followed by hands-on walkthrough for predicting protein structures,docking and protein designing.


    Rosetta is a set of tools used for protein structure prediction and designing. Rosetta is capable of predicting structures either with or without prior knowledge. Apart from large and small molecular docking, Rosetta is also popular for designing novel proteins and peptides. With the availability of public cloud infrastructure, use of Rosetta's powerful features is within the reach of anyone who is interested in molecular modeling and design.


    • Participants will work in a linux desktop environment.
    • Participants will also receive a cookbook style manual for all the hands-on exercises.
    • After training support is also provided through exclusive members only forum.

    Nov. 18-21, 2019
    San Diego, CA, USA
    IEEE BIBM Workshop on Expository Representation Learning of Biomedical Data (ERLBD) to be held in conjunction with the 2019 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2019):

    In today's world data is produced at a mind-boggling volume and pace. According to marketing reports 90 percent of the data in the world was produced within the past two years. With the recent advances in high-throughput technologies, OMICS data in the biomedical field would be one of the biggest contributor to this everlasting growth. These large volumes of data are widely accessible; however, they are mostly unstructured while having the potential to deepen our understanding of complex problems from disease outbreak to disease diagnosis and treatment. Statistical and machine learning methods can help expose the hidden value of unstructured data, improving prediction accuracy, and build predictive models that go beyond human performance. Recently, there is a surge of new techniques in the context of discovering latent structure in high dimensional data such as causal relations in multifaceted regulation networks, genotype and phenotype association, genomics signatures, and risk factors etc. However, it can still be a long way to obtain satisfactory results in scalable learning with increasing data size and complexity. Furthermore, a wide variety of technologies produce heterogeneous data shedding light on different aspects of complex biological systems. Emergence of a more complete picture of biological systems depends on successful methods for integration of data from these different perspectives. With this workshop, we aim to encourage researchers to develop new methodologies, analytical models, and high-throughput computing workflow that best utilize various types of biomedical data in ways that meaningful structures present but hidden in data can be revealed.


    The potential topics include, but not limited to, the following:
    • Data-centric models for diagnosis and classification of complex human disease such as cancers and obesity
    • Learning based prediction models for drug response assessment
    • Integrative models for identification of dynamic and multi-level biological interaction networks (proteins, non-coding genes, metabolites)
    • Integrative models for discovery of disease associated cell communication
    • Complex phylogenetic models to elucidate cancer genome evolution
    • High-throughput computing workflow development for data mining, visualization, and interpretation
    • High-throughput computing workflow development for biomedical image processing classification
    • Integrative models for visualization and analysis of data in neuroscience
    • Information fusion based modeling for reverse engineering biological networks
    • Inferring genomic signatures from sequencing and expression data
    • Modeling and simulation of complex biological processes in high-throughput computing environments


    We invite you to submit papers with unpublished, original research describing recent advances on the areas related to this workshop. All papers will undergo peer review by the conference program committee. All papers accepted will be included in the Workshop Proceedings published by the IEEE Computer Society Press and will be available at the workshops. Authors of selected papers will be invited to extend their papers for submission to special issues in prestigious Journals.

    Paper Submission:
    Please submit a full-length paper (up to 8 pages in IEEE two-column format) through the online submission system. Electronic submissions in pdf format are required.

    For paper submission click on the following link:[...]t.php


    Funds are available for limited travel fellowships to support students and researchers from underrepresented minority groups.


    Due date for full workshop paper submission: October 01, 2019 11:59:59 PM EST
    Notification of paper acceptance to authors: Oct 15, 2019
    Camera-ready of accepted papers: Nov 1, 2019
    Workshops: Nov 18-21, 2019

    Workshop Chair: Juan Cui
    Education: Course on Comparative Genomics (2nd edition)
    Submitted by Carlo Pecoraro; posted on Friday, September 06, 2019


    October 7-11, 2019
    Free University Berlin, Germany[...]se34/


    We will cover a broad range of software and analysis workflows that extend over the spectrum from assembling and annotating eukaryotic genomes, via the identification of single nucleotide variants (SNVs) and structural variants (SVs) within the population, to the assessment of their likely functional impact of the detected variants in an evolutionary context.


    The course is aimed at researchers interested in learning how to compare genomes and what can be learned from genomic similarities as well as variations. It will include information useful for both beginners and more advanced users. We will start by introducing general concepts of comparative genomics. On this basis, we will then continue to describe all major analysis steps from the raw sequencing data via the identification of variations to an assessment of their impact on the phenotype.

    Attendees should have a background in biology. There will be a mix of lectures and hands-on practical exercises using command line Linux. We will therefore dedicate one session to introduce basic and advanced Linux concepts for processing data on Amazon cloud (AWS). Attendees should have also some familiarity with genomic data such as that arising from NGS sequencing experiments.


    • Setting up a comparative genomics analysis environment with the CONDA package management system
    • Identification of SNPs and SVs using de novo genome assembly and read mapping strategies
    • Assessment of strengths and weaknesses of the different DNA sequencing technologies, Illumina, Pacific Bioscience, Oxford Nanopore, for the detection of variations
    • Strengths and pitfalls of de novo assembly and mapping approaches for comparative genomics
    • Hands on experience of state of the art methods to compare multiple genomes
    • Annotation of variations and comparative genomics analysis
    • Familiarity with biological sequence analysis in an evolutionary context


    Dr Fritz J. Sedlazeck (
    Prof. Dr. Ingo Ebersberger ([...]hl=en)

    For more information about the course, please visit our website.

    Here is the full list of our courses and Workshops:

    September 23-27, 2019
    Glasgow City Centre, Scotland, UK[...]ms01/

    This course will be delivered by Dr. Mark Andrews.


    Python is one of the most widely used and highly valued programming languages in the world, and is especially widely used in data science, machine learning, and in other scientific computing applications. This course provides both a general introduction to programming with Python and a comprehensive introduction to using Python for data science, machine learning, and scientific computing. The major topics that we will cover include the following: the fundamentals of general purpose programming in Python; using Jupyter notebooks as a reproducible interactive Python programming environment; numerical computing using numpy; data processing and manipulations using pandas; data visualization using matplotlib, seaborn, ggplot, bokeh, altair, etc; symbolic mathematics using sympy; data science and machine learning using scikit-learn, keras, and tensorflow; Bayesian modelling using PyMC3 and PyStan; high performance computing with Cython, Numba, IPyParallel, Dask. Overall, this course aims to provide a solid introduction to Python generally as a programming language, and to its principal tools for doing data science, machine learning, and scientific computing. (Note that this course will focus on Python 3 exclusively given that Python 2 has now reached it end of life).


    The course fees are £550 and the first five applicant will receive free accommodation for the week, breakfast and lunch.
    Education: Training in Bioinformatics for Beginners @ NIH
    Submitted by Vijayaraj Nagarajan; posted on Friday, August 30, 2019

    October 1-4, 2019
    National Institutes of Health
    9000 Rockville Pike
    Building 60, Room 162
    Bethesda, MD 20892, USA


    The participants will be provided with end-to-end hands-on training, along with introduction to basic concepts, in using popular tools and techniques for sequence analysis, structure analysis, function prediction, biological database searching, "omics" data analysis, pathway analysis, data visualization, data curation and integration, linux, R, perl and scripting basics.


    Bioinformatics (Computational Biology) is a must skill required in every modern biomedical research lab. Installing and configuring a wide variety of computational biology tools is a cumbersome task that requires software engineering skills. This hands-on training course will introduce participants to a comprehensive set of bioinformatics concepts, tools and techniques, using a cloud based, all-in-one, fully loaded linux desktop (with windows like graphical user interface) machine, that comes with hundreds of popular computational biology (bioinformatics) tools required for a successful modern biomedical research lab.


    • Participants will use a Graphic User Interface based Linux Desktop environment, specially configured for bioinformatics analysis in the Amazon Cloud
    • Training provided by experienced active NIH researchers
    • Cookbook style bound manual for all exercises
    • Direct, after training support through exclusive forum membership
    • Continuing Educational Credits
    Hands-on Skills/Tools Taught:
    • Databases: NCBI-ENTREZ, UniProt, PDB, STRING, Others
    • Sequence analysis and function predictions: EMBOSS suite & others
    • Local Alignment: EMBOSS-WATER
    • Global Alignment: EMBOSS-NEEDLE
    • Similarity search: NCBI BLAST, PSI-BLAST
    • Multiple sequence alignment: Clustal Omega, MUSCLE, MAFFT
    • Phylogenetics: MrBayes, MEGA, FigTree and Dendroscope
    • Motif finding, analysis: MEME suite
    • Structure prediction, visualization & analysis: PyMOL, Chimera, iTASSER
    • Transcriptome analysis: NCBI GEO, Tuxedo tools, R
    • Enrichment analysis: DAVID
    • Pathway analysis: Cytoscape
    • Programming: R, Perl, Python
    • Platforms: EMBOSS, UGENE, H2O, Galaxy
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