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Rescooped by Pedro Fernandes from Digital Delights for Learners
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GUIDES for iPads

GUIDES for iPads | Bioinformatics Training | Scoop.it
Making iPad resources with a Windows PC. Transition to teaching with devices: Step 1 iPad workflow and collaboration for Schools Google docs are live docs with no further uploading/emailing require...

Via Ana Cristina Pratas
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Rod Murray's curator insight, July 11, 2013 9:50 AM

Some rich resources and how-tos here! for how to make the tranistion to digital classroom using iPad

netquester's comment, July 15, 2013 3:50 PM
Useful tips for good use of iPads
netquester's curator insight, July 15, 2013 3:50 PM

A good blog to follow

 

Bioinformatics Training
Bioinformatics, blended with education and health sciences subjects
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GTPB: PGDH15 - Population Genetics and Demographic History: model-based approaches - July 6th-9th

GTPB: PGDH15 - Population Genetics and Demographic History: model-based approaches - July 6th-9th | Bioinformatics Training | Scoop.it
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Course description

Genetic data are increasingly used by ecologists and evolutionary biologists in general. It has thus become important for many biologists with different levels of experience to produce and analyse genetic (and genomic) data. In this course we will take a practical approach to the analysis of genetic data, but we will also provide some of the theoretical background required to understand the outputs of the software used. This course will be organised so as to mix lectures where important notions are introduced with practicals where freely available software will be used. While this will not be the focus of the course, we will also introduce and discuss genealogical (coalescent-based) simulation methods and those based on forward-in-time simulations. Altogether this will allow to discuss the potentialities and limitations of the tools available to the community.

In this four-day course we will introduce the main concepts that underlie many of the models that are frequently used in population genetics. We will focus on the importance of demographic history (e.g. effective sizes and migration patterns) in shaping genetic data. We will go through the basic notions that are central to population genetics, insisting particularly on the statistics used to measure genetic diversity and population differentiation. The course will also cover a short introduction to coalescent theory, Bayesian inference in population genetics and data simulation, as they are connected to what makes landscape genetics today on the basis of multilocus data. We will also introduce two methods that have been recently developed to analyse genomic data. The PSMC of Li and Durbin reconstructs the demographic history of a species or population with the genome of a single individual. The Rehh package is an R implementation of the Extended Haplotype Homozygosity (EHH) test for selective sweeps and looks for signals of selection based on the analysis of genomic regions.

Most theory will be put into practice in practical sessions, analyzing real and/or simulated datasets. In these sessions, we will look at measures of genetic diversity and differentiation and use methods to detect population structure as implemented in the program STRUCTURE and discuss related programs such as FastSTRUCTURE. We will learn how to perform coalescent simulations of genetic data (using SPAms and ms). Some exercises will make use of R scripts (R being a freely available statistical program). Basic R knowledge is a pre-requisite but we will provide a short introduction to R. The R statistical package is a very powerful tool to analyse data outputs from many population genetics software, and can also be used to simulate genetic data under simple demographic scenarios.

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GTPB: BPBR15 Bioinformatics using Python for Biomedical Researchers - July 20th-24th

GTPB: BPBR15 Bioinformatics using Python for Biomedical Researchers - July 20th-24th | Bioinformatics Training | Scoop.it
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Course Description

Python is an object-oriented programming language that is ideal for biological data analysis. The course will start from zero knowledge, and will introduce the participants to all the basic concepts of Python such as calculating, organizing data, reading and writing files, program logic and writing larger programs. All the examples and practical sessions will focus on solving biological problems. In particular the sessions will cover:

working with DNA and protein sequencesdata retrieval from files and their manipulationrunning applications, such as BLAST, locally and from a scriptfinding motifs in sequenceparsing common file formats (Uniprot, GenBank, PDB, BLAST) with Biopythonways to find and correct program errors

The course will be highly interactive and the students will continuously put theory into practice while learning. By the end of the course, the participants will have a good understanding of Python basics and will have acquired the skills to manage any type of bioinformatics database record and to run applications from scripts. Basic Unix/Linux skills will be provided at the beginning of the course. Target Audience End-users of bioinformatics databases and tools that aim at developing hands-on capabilities for biological data analysis, ie writing their own or adapting somebody else's Python scripts in an autonomous way. Course Pre-requisites Basic familiarity with bioinformatics data resources such as Uniprot/Swiss-Prot, Blast, ENSEMBL, PDB, etc. The course is directed to biologists with little or no programming experience and aims at making them capable to use Python to autonomously manage and analyse biological data.

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Rescooped by Pedro Fernandes from Bioinformatics Software: Sequence Analysis
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Hybrid De Novo Genome Assembly Using MiSeq and SOLiD Short Read Data

Hybrid  De Novo  Genome Assembly Using MiSeq and SOLiD Short Read Data | Bioinformatics Training | Scoop.it
A hybrid de novo assembly pipeline was constructed to utilize both MiSeq and SOLiD short read data in combination in the assembly.

Via Mel Melendrez-Vallard
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Rescooped by Pedro Fernandes from PDF Magazines Free Download
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Computational and Visualization Techniques for Structural Bioinformatics Using Chimera

Computational and Visualization Techniques for Structural Bioinformatics Using Chimera | Bioinformatics Training | Scoop.it
Computational and Visualization Techniques for Structural Bioinformatics Using Chimera shows how to perform computations with Python scripts in the Chimera environment.

Via eBooklyn
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Global Bioinformatics Market 2015 2019

Link to Report: https://www.youtube.com/watch?v=yNaL15zWuv4&feature=youtu.be Technavio's report, Global Bioinformatics Market 2015-2019, has been ...
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Translational bioinformatics Meaning

Video shows what translational bioinformatics means. The branch of bioinformatics that uses genomic data as its source. Translational bioinformatics Meaning.
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IonGAP: integrative bacterial genome analysis for Ion Torrent sequence data

IonGAP: integrative bacterial genome analysis for Ion Torrent sequence data | Bioinformatics Training | Scoop.it
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Rescooped by Pedro Fernandes from Virology and Bioinformatics from Virology.ca
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Experimental Evolution of an RNA Virus in Wild Birds: Evidence for Host-Dependent Impacts on Population Structure and Competitive Fitness

Experimental Evolution of an RNA Virus in Wild Birds: Evidence for Host-Dependent Impacts on Population Structure and Competitive Fitness | Bioinformatics Training | Scoop.it
Author Summary Viruses are constantly emerging into new areas and pose significant challenges to public health.

Via Ed Rybicki
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Rescooped by Pedro Fernandes from Virology and Bioinformatics from Virology.ca
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Influenza A virus utilizes a suboptimal Kozak sequence to fine-tune virus replication and host response

The segment-specific non-coding regions (NCRs) of influenza A virus RNA genome play important roles in controlling viral RNA transcription, replication and genome packaging. In this report, we present, for the first time to our knowledge, a full view of the segment-specific NCRs of all influenza A viruses by bioinformatics analysis. Our systematic functional analysis revealed that the eight segment-specific NCRs identified could differentially regulate viral RNA synthesis and protein expression at both transcription and translation levels. Interestingly, a highly conserved suboptimal nucleotide at −3 position of the Kozak sequence, which downregulated protein expression at the translation level, was only present in the segment-specific NCR of PB1. By reverse genetics, we demonstrate that recombinant viruses with an optimized Kozak sequence at the −3 position in PB1 resulted in a significant multiple-cycle replication reduction that was independent of PB1-F2 expression. Our detailed dynamic analysis of virus infection revealed that the mutant virus displays slightly altered dynamics from the wild-type virus on both viral RNA synthesis and protein production. Furthermore, we demonstrated that the level of PB1 expression is involved in regulating type I IFN production. Together, these data reveal a novel strategy exploited by influenza A virus to fine-tune virus replication dynamics and host antiviral response through regulating PB1 protein expression.


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Bioinformatics algorithms for the reconstruction of consensus trees and multiple supertrees

UQAM's Nadia Tahiri at the May-2015 MonBug meeting at the IRCM in Montreal.
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GTPB: ABSTATB15 - Advanced Biostatistics for Biologists - July 13th-17th

GTPB: ABSTATB15 - Advanced Biostatistics for Biologists - July 13th-17th | Bioinformatics Training | Scoop.it
Pedro Fernandes's insight:

Course description

This course is a standalone advanced Biostatistics course that can be taken as a continuation of the Introductory Biostatistics for Bioinformatics (IBSTAT) course, that precedes it in GTPB. It is targeted for Biostatistical techniques often employed in analytical tools for high throughput data and multivariate data. Participants can expect to attend a thorough set of lectures that will reveal the conceptual frameworks that are needed to understand the methods. Extensive hands-on practice will be the main vehicle for providing the skills and user independence. To keep things in context, the course is exclusively based on biological examples, worked with Bioinformatics tools.
Care has been taken not to use any proprietary data or software, so that the hands-on experience can carry on after the course, providing maximum user independence. We will be using custom-built R scripts and packages that are available from the CRAN and Bioconductor repositories.

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Coding Boot Camps Are on the Rise

Coding Boot Camps Are on the Rise | Bioinformatics Training | Scoop.it
The unaccredited education programs known as coding boot camps are proliferating, and gaining more students.
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Rescooped by Pedro Fernandes from Bioinformatics Software: Sequence Analysis
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A novel statistical method for quantitative comparison of multiple ChIP-seq datasets

A novel statistical method for quantitative comparison of multiple ChIP-seq datasets | Bioinformatics Training | Scoop.it
Another method for quantitative comparison of multiple ChIP-seq datasets http://t.co/Z6wm6kHwkU w/ #Rstats pkg

Via Mel Melendrez-Vallard
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OpenHelix for bioinformatics software training

Knowing which tools are available, and learning to use them, can be challenging in genomics. The OpenHelix site connects you to information and software ...
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BMC Genomics | Full text | Global transcription of CRISPR loci in the human oral cavity

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) are active in acquired resistance against bacteriophage and plasmids in a number of environments.
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Improving bioinformatics accessibility with the GenAP Portal

McGill's David Bujold at the May-2015 MonBug meeting at the IRCM in Montreal.
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