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14 materials found

Authors: allegra.via Via  or Marta Lloret Llinares 

FAIR software tools

In this talk, I will discuss the importance of the FAIR principles for the software tools we use to process data. Ranging from small analysis scripts to full fledged data processing pipelines, software needs to be FAIR to enable other researchers to reproduce our own experiments and reuse our...

Scientific topics: Software engineering

Keywords: FAIR, software tools, Software

Resource type: Video

Making cohort data FAIR

Cohort studies, which recruit groups of individuals who share common characteristics and follow them over a period of time, are a robust and essential method in biomedical research for understanding the links between risk factors and diseases. Through questionnaires, medical assessments, and...

Scientific topics: Data management, Data integration and warehousing

Keywords: FAIR data, Cohort data, Ontologies, Standards

Resource type: Video

Introduction to FAIR principles - Open science through FAIR health data networks: dream or reality?

Since the FAIR data principles were published in 2016, many organizations including science funders and governments have adopted these principles to promote and foster true open science collaborations. However, to define a vision and create a video of a Personal Health Train that leverages...

Scientific topics: Data management

Keywords: FAIR data, Health data, Open science

Resource type: Video

Data Gravity in the Life Sciences: Lessons learned from the HCA and other federated data projects

We live in an era of cloud computing. Many of the services in the life sciences are keenly planning cloud transformations, seeking to create globally distributed ecosystems of harmonised data based on standards from organisations like GA4GH. CINECA faces similar challenges, gathering cohort...

Scientific topics: Data architecture, analysis and design

Keywords: Cloud computing, Data analysis, Standards, Translational research

Resource type: Video

Status Update Code of Conduct: Teaming up & Talking about it

Committed to the drafting of a Code of Conduct for the sector of health research according to Art. 40 GDPR, our initiative is advancing slowly but steadily. Throughout Europe, national jurisdictions differ to a great deal in their interpretations of the GDPR, especially in regard to its...

Keywords: GDPR, Healthcare research, data harmonization

Resource type: Video

Introduction to Biopython

This is a module from the "Python for Biologists" course. The module presents an introduction to Biopython. It shows how to deal with sequences and sequence records, how to download records from NCBI databases, how to run Blast and how to parse XML Blast outputs.

Keywords: Bioinformatics, Biopython, Programming, Python, Python biologists

Using R with Python

This is a module from the "Python for Biologists" course. It describes the Python module interfacing the R package for statistics. The module shows how to calculate mean, standard deviation, z-score and p-value of a set of numbers, and how to generate plots. Input files for the scripts presented...

Keywords: Programming, Python, Python biologists

Searching data using Python

This is a module from the "Python for Biologists" course. It describes how to use Python dictionary and set data structures to search your data. In particular, how to use a dictionary to represent the genetic code table and use it to translate a nucleotide sequence into a protein sequence, and...

Keywords: Programming, Python, Python biologists

Pattern Matching

This is a module from the "Python for Biologists" course. It teaches how to do pattern matching in Python, i.e. how to find a substring (or a set of substrings) in a string. To this aim, it introduces the regular expression syntax, and the tools needed to search regular expressions in biological...

Keywords: Pattern matching, Programming, Python, Python biologists

Writing functions in Python programming

This is a module from the "Python for Biologists" course. It deals with functions and how to write and use them. It also introduces namespaces and the tuple data structure. The module contains several exercises and suggested solutions. The text of exercises is also provided in a separate file. 

Scientific topics: Bioinformatics

Keywords: Programming, Python, Python biologists

Python Programs

This is a module from the "Python for Biologists" course. It deals with Python programs, how to write and run them, and how to provide input and generate output. The module also contains exercises and suggested solutions. 

Keywords: Programming, Python, Python biologists

Linear Motifs and Phosphorylation Sites

This is a lecture on linear motifs and phophorylation sites (P-sites). Some materials from other lectures are reused.
The lecture is basically about computational approaches to encode, predict, analyse, and use functional motifs and P-sites.
Here you can find:

    A definition of linear motifs and...

Keywords: Bioinformatics

Parsing data records using Python programming

This is a module from the "Python for Biologists" course. One typical problem in bioinformatics is parsing data files. This module explains how to parse FASTA files and GenBank records. It also introduces the if/elif/else construct to make choice in programming and the list  data structure. The...

Keywords: Bioinformatics, Programming, Python, Python biologists, Record parsing

Introduction to Unix

Introductory lecture to the Unix/Linux command-line

    Description of the computer shell and the command-line interface

    Differences between graphical and command-line interfaces

    The most commond Unix/Linux commands are provided


Keywords: Bioinformatics, Programming, Unixlinux