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Venue
- European Bioinformatics Institute, Hinxton6
- , 3
- Narva mnt 18, room 20213
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- Bioinformaticians and Biologists who want to learn how to manipulate, process data, and make plots using R1
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- This course is aimed at individuals working across life sciences who have little or no experience in bioinformatics. Applicants are expected to be at an early stage of using bioinformatics in their research with the need to develop their knowledge and skills further. No previous knowledge of programming is required for this course; group projects may give you the opportunity to learn basic programming, but participants will be supported in this by their mentors. Depending on your chosen project, an introductory programming tutorial may be given as homework prior to attending the course.1
- This course is targeted at biologists who want to explore, and gain further insight, into their own data through the use of visualisation and design approaches. Some prior experience in programming would be beneficial, but pre-reading and exercises will be sent out to all successful applicants prior to the start of the course. Example datasets will be provided which include: gene-gene interaction data gene-disorder links phylogeny of transcription factors ChIP-Seq and RNA-Seq1
- This introductory course is aimed at biologists who are embarking on multiomics projects and computational biologists / bioinformaticians who wish to gain a better understanding of the biological challenges when working with integrated datasets. No programming or command line experience is required to attend this course. Please note this course does not cover statistical approaches for data integration. For advanced-level training in using large-scale multiomics data and machine learning to infer biological models you may wish to consider our course on Systems Biology: From large datasets to biological insight.1
- This introductory course is aimed at biologists who are embarking on multiomics projects and computational biologists/bioinformaticians who wish to gain a better knowledge of the biological challenges presented when working with integrated datasets. Some practical sessions in the course require a basic understanding of the Unix command line and the R statistics package. If you are not already familiar with these then please ensure that you complete these free tutorials before you attend the course: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Basic R concept tutorials: www.r-tutor.com/r-introduction1
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Language
- English1
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Instructor
- Lee Larcombe3
- Nikiforos Karamanis3
- Alex Bateman2
- Anna Swan2
- Baron Koylass2
- Hedi Peterson2
- Jan Aerts2
- Priit Adler2
- Ryo Sakai2
- Sandra Orchard2
- Adam Frost1
- Ajay Mishra1
- Alexandra Holinski1
- Amanda M. Saravia-Butler1
- Andrew Jarnuczak1
- Asier Gonzalez1
- Aurelien Dugourd1
- Aybuke Kupcu Yoldas1
- Boris Adryan1
- Britta Velten1
- Claire O’Donovan1
- Danila Bredhkin1
- David Armstrong1
- David Fazekas1
- Dayane Rodrigues Araujo1
- Dezso Modos1
- Elena Lukyanova1
- Francesco Iorio1
- Gaurhari Dass1
- Girolamo Giudice1
- Hanna Najgebauer1
- Helena Cornu1
- Hema Bye-A-Jee1
- James Tolchard1
- Jannes Peeters1
- Jelmer Bot1
- Johannes Griss1
- John Berrisford1
- Kausthubh Ramachandran1
- Konstantinos Tsirigos1
- Krishna Kumar Tiwari1
- Krishna Tiwari1
- Loïc Lannelongue1
- Marcus Bage1
- Maria Zimmermann1
- Marta Lloret Llinares1
- Marton Olbei1
- Masa Roller1
- Michaela Spitzer1
- Michal Szpak1
- Monica Abrudan1
- Nils Eling1
- Pablo Porras Millan1
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- Ricard Argelaguet1
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- Selene L. Fernandez-Valverde1
- Shila Ghazanfar1
- Tamas Korcsmáros1
- Tamás Korcsmáros1
- Teresa Zulueta-Coarasa1
- Yasset Perez Riverol1
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