A brief tutorial on how to install and update packages in R
GenomeSearch is the first Android application that Edwards' Lab has developed. It is a simple Bioinformatics Search which queries theSEED.org for a genome and keyword, and returns search results with links to reference material. Note that in this video, the mouse cursor simulates what a users touch would do on a real phone.
For more information about Dr. Rob Edwards' Lab and projects our team is currently working on, please visithttp://edwards.sdsu.edu/labsite/index...
The eIUS Project highlights the successful use of e-Infrastructure, in this case by researchers in Bioinformatics at the University of Manchester who, in collaboration with the myGrid Consortium, use the Taverna Workbench and the myExperiment virtual research environment to assist with the analysis and sharing of data relating to sleeping sickness (Trypanosomiasis) in African cattle. The eIUS Project is funded by the JISC and supported by the University of Oxford and University of Manchester.
There is an urgent need to translate genome-era discoveries into clinical utility, but the difficulties in making bench-to-bedside translations haven't been well described. The nascent field of translational bioinformatics may help. Dr. Butte's lab at Stanford University builds and applies tools that convert more than 300 billion points of molecular, clinical, and epidemiological data (measured by researchers and clinicians over the past decade) into diagnostics, therapeutics, and new insights into disease. Dr. Butte, a bioinformatician and pediatric endocrinologist, will highlight his lab's work on using publicly available molecular measurements to find new uses for drugs, discovering new treatable mechanisms of disease in type 2 diabetes, and evaluating patients presenting with whole genomes sequenced.
The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide.
A brief overview of Bioinformatics career opportunities brought to you by the University of South Dakota Computer Science Department
Were going to go over calculating GC content and making your first Python Program, So if you're a little more advanced and you already know how to use Python, but you'd like to learn more, go ahead and click the link below where I'll show you advanced techniques in learning python for bioinformatics.
The first thing we're going to need is some data. If you don't have any data, you can't do any bioinformatics, but the great thing is, is there is a ton of free data online ready to go.
So go ahead and open up your web browser and lets get started, I use chrome.
Go ahead and type in the Letters NCBI. In the search bar go ahead and type in BRCA 1
Click on this little tab right here that says nucleotide. Up at the top we've got a few things, go ahead and click on the homo sapiens BRCA1, FASTA tab.
Click on Send in the top right hand corner, click on send to file, and download as FASTA. Then copy that sequence.fasta to a new folder we'll be working in. Replace the name to BRCA1_BAP1.TXT, then you can open it and look at it
