|
|
|
3DAROC20 3C-based data analysis and 3D reconstruction of chromatin foldingDownloadable poster in PDF |
|
IMPORTANT DATES for this Course Deadline for applications:
March 18th 2020
|
Instructors: |
|
Affiliation: Centro Nacional de Análisis Genómico (CNAG) and Center for Genomic Regulation (CRG), Barcelona, ES |
|
Affiliation: Centro Nacional de Análisis Genómico (CNAG) and Center for Genomic Regulation (CRG), Barcelona, ES |
|
Affiliation: Centro Nacional de Análisis Genómico (CNAG) and Center for Genomic Regulation (CRG), Barcelona, ES |
Course description
3C-based methods, such as Hi-C, produce a huge amount of raw data as pairs of DNA reads that are in close spatial proximity in the cell nucleus. Overall, those interaction matrices have been used to study how the genome folds within the
nucleus, which is one of the most fascinating problems in modern biology. The rigorous analysis of those paired-reads using computational tools has been essential to fully exploit the experimental technique, and to study how the genome is
folded in space. Currently, there is a clear expansion on the wealth of data on genome structure with the availability of many datasets of Hi-C experiments down to 1Kb resolution (see for example: In this course, participants will learn to use TADbit, a software designed and developed to manage all dimensionalities of the Hi-C data:
|
Target AudienceThe course design is oriented towards experimental researchers and bioinformaticians at the graduate and post-graduate levels. The last edition of this course was attended by people with different backgrounds and interested in the genome organization. It is likely that the participants to this course aim at getting involved in generating Hi-C data for chromosome structure determination or that they just want to be able to correctly interpret and analyse publicly available data. |
SponsorshipCOST Action CA18127 (International Nucleome Consortium, @INC_COST)A number of travel and subsistence grants is available for accepted course participants applying from counties that run COST actions. Participants from:
  Funded by the Horizon 2020 Framework Programme of the European Union
|
Course Pre-requisitesRecommended Linux and basic Python programming skills, graduate level in Life Sciences. TADbit APIThis tutorial is associated with a specific version of TADbit. if you wish to reproduce exactly the results you should use the version of TADbit tagged 3DAROC_2020. To install this version, please issue these commands: git clone https://github.com/3DGenomes/TADbit cd tadbit git checkout tags/3DAROC_2020 sudo python setup.py install TADbit toolsMost of the tasks of the "core pipeline" can be tunned directly from command line (without any python), using TADbit tool. Have a look to the commands, and the metadata of the results. TADbit page at github: https://github.com/3DGenomes/TADbit |
|
Applications |
|
Detailed Program |
|
Instituto Gulbenkian de Ciência, Apartado 14, 2781-901 Oeiras, Portugal Last updated: February 27th 2020 |
Marc A. Martí-Renom obtained a PhD in Biophysics from the Universidad Autonoma de Barcelona (UAB) where he worked on protein folding under the supervision of B. Oliva, F.X. Aviles and M. Karplus (Nobel Laureate for Chemistry
2013). After that, he went to the US for a postdoctoral training on protein structure modelling at the Sali Lab (Rockefeller University) as the recipient of the Burroughs Wellcome Fund fellowship. Later on, Marc was appointed Assistant
Adjunct Professor at UCSF. Between 2006 and 2011, he headed the Structural Genomics Group at the CIPF in Valencia (Spain). Currently, Marc is an ICREA research professor and leads the Structural Genomics Group at the National Center for
Genomic Analysis - Centre for Genomic Regulation (CNAG-CRG) in Barcelona. His research group employs the laws of physics and the rules of evolution to develop and apply experimental and computational methods for elucidating the 3D
structures of macromolecules and their complexes. Between 2012 and 2018, Marc was an Associate Editor of the PLoS Computational Biology journal and has published over 100 articles in international peer-reviewed journals. He coordinated
two international teams funded by the EU (Era-Net Pathogenomics Grant) and the HFSP (Research Grants Award). Since 2014, he became the co-PI on the 4DGenome Grant funded by the ERC Synergy program as well as the co-PI on the MuG
Research project funded by the European Commission H2020 program. In the last few years, Marc played a key role in Europe to promote the 
Marco Di Stefano obtained his Ph.D. in Biophysics in 2014 (Scuola Internazionale Superiore di Studi Avanzati: Trieste, Friuli-Venezia Giulia, IT) working on Physics-based structural models of chromosomes to study the
relationship between gene co-expression and gene co-localization. He moved as a post-doctoral researcher to the structural genomics group of Marc Marti-Renom at CNAG-CRG (Barcelona). His main research interest is in integrating
chromosome conformation capture data, epigenomics, and polymer Physics to study constitutive mechanisms of chromosome folding. He has been involved in GTPB as an instructor for 3DAROC16 - 3C-based data analysis and 3D reconstruction of
chromatin folding.
David Castillo obtained his MSc in Photonics from the Universitat Politècnica de Catalunya in Barcelona (Spain) where he worked in Super-resolution microscopy. He has a background in Physics and Engineering. He works as a
technician in the Structural Genomics team of Marc A. Martí-Renom at CNAG-CRG (Barcelona), developing tools for the analysis, modelling and visualization of Hi-C data. David is also interested in the integration of microscopy into the
modeling of genomic 3D structures.He has been involved in GTPB as an instructor for 3DAROC18 - 3C-based data analysis and 3D reconstruction of chromatin folding.