The immune response to HIV Poster

http://www.nature.com/nri/posters/hiv/index.html

The immune response to HIV

Nina Bhardwaj, Florian Hladik and Susan Moir

Article body

A global research effort over the past three decades has discovered more about HIV than perhaps any other pathogen. Immunologists continue to be intrigued by the capacity of HIV to effectively knock out an essential component of the adaptive immune system — CD4⁺ T helper cells. Based on a clearer understanding of HIV infection and the response to it, the field has now entered an era of renewed optimism for the development of a successful vaccine.

This Poster summarizes how HIV establishes infection at mucosal surfaces, the ensuing immune response to the virus involving dendritic cells, B cells and T cells, and how HIV subverts this response to establish a chronic infection.

The Poster is freely available thanks to support from STEMCELL Technologies.

Interactome3D: adding structural details to protein networks

http://www.nature.com/nmeth/journal/v10/n1/full/nmeth.2289.html?WT.ec_id=NMETH-201301

 Interactome3D: adding structural details to protein networks

• Roberto Mosca,
• Arnaud Céol
• & Patrick Aloy

• Affiliations
• Contributions
• Corresponding author

Nature Methods

 

10,

 

47–53

 

(2013)

 

doi:10.1038/nmeth.2289

Received

 

18 July 2012 

Accepted

 

30 October 2012 

Published online

 

16 December 2012

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Abstract

• Abstract
• Introduction
 
• Results
 
• Discussion
 
• Methods
 
• Accession codes
 
• References
• Acknowledgments
 
• Author information
 
• Supplementary information

Network-centered approaches are increasingly used to understand the fundamentals of biology. However, the molecular details contained in the interaction networks, often necessary to understand cellular processes, are very limited, and the experimental difficulties surrounding the determination of protein complex structures make computational modeling techniques paramount. Here we present Interactome3D, a resource for the structural annotation and modeling of protein-protein interactions. Through the integration of interaction data from the main pathway repositories, we provide structural details at atomic resolution for over 12,000 protein-protein interactions in eight model organisms. Unlike static databases, Interactome3D also allows biologists to upload newly discovered interactions and pathways in any species, select the best combination of structural templates and build three-dimensional models in a fully automated manner. Finally, we illustrate the value of Interactome3D through the structural annotation of the complement cascade pathway, rationalizing a potential common mechanism of action suggested for several disease-causing mutations.

An indirect approach to generating specific human cell types

http://www.nature.com/nmeth/journal/v10/n1/full/nmeth.2325.html?WT.ec_id=NMETH-201301

Two groups derived neural and mesodermal cells from human fibroblasts by going through a partially reprogrammed intermediate.

Subject terms:

• Stem Cells
• Cell Biology
• Genetics

The ability to easily convert accessible human cells into disease-relevant cell types through cellular reprogramming has opened new doors for basic research and regenerative medicine¹. Takahashi and Yamanaka ushered in contemporary reprogramming when they demonstrated that a combination of four transcription factors (Oct3/4, Sox2, Klf4 and c-Myc) could drive skin-derived fibroblasts to a pluripotent state that could be further differentiated into the desired cell type² (Fig. 1a). But robust differentiation into specific lineages remains a stumbling block. Low efficiencies and week- to month-long protocols often give rise to mixed cultures requiring a second purification step. Purity matters, as remnant pluripotent cells can give rise to tumors after transplantation. Moreover, the yielded cells are typically immature (as in cardiomyocyte, hematopoietic or neuronal differentiation).

UnitedHealth, Mayo Clinic to open big-data research lab in Cambridge

The Wall Street Journal reports thatUnitedHealth Group Inc. (NYSE: UNH) of Minnetonka and the Rochester-basedMayo Clinic will form Optum Labs, which UnitedHealth CEO Stephen Hemsley called a "dedicated research unit" that could study things such as improving diagnosis of Hepatitis C or the effectiveness of hip-replacement surgery.

IHI Open School: UBC Chapter

http://www.ihi.org/offerings/IHIOpenSchool/GetInvolved/Pages/default.aspx

http://blogs.ubc.ca/ihiopenschool/

The Institute for Healthcare Improvement (IHI), an independent not-for-profit organization based in Cambridge, Massachusetts, is a leading innovator in health and health care improvement worldwide. At our core, we believe everyone should get the best care and health possible. This passionate belief fuels our mission to improve health and health care.

pdf to word, OCR

• abiword
• poppler-utils
• http://faceted.wordpress.com/2010/07/11/how-to-extract-text-from-pdf-files-using-poppler-and-gocr-on-ubuntu/ 
•  pdftotext foo.pdf
•  pdfimages foo.pdf foo-page
•  for i in *pbm; do echo gocr $i; gocr $i > $i.txt; done (OCR)
•  tesseract-ocr
• Adobe Acrobat Pro

Andrew Schwartz: Brain Control for Artificial Limbs

http://www.businessweek.com/articles/2013-01-10/andrew-schwartz-brain-control-for-artificial-limbs

When Jan Scheuermann grasped a chocolate bar and raised it to her mouth last year, it was a neuroscience breakthrough. Scheuermann, who has lost the movement of her limbs due to a degenerative spinal condition, was piloting a mechanical arm connected to her brain, using her thoughts to replicate natural motion.

InteraXon
http://www.youtube.com/watch?v=bC2vDrhxH_0 
http://www.businessweek.com/articles/2012-10-23/mind-over-machine-use-your-brain-waves-to-control-your-computer#r=lr-fs 
When it comes to controlling our computers, the last five years has seen incredible improvements in user interfaces including amazing touchscreens and much more natural vocal recognition. Now a Toronto company wants to take the UI to the next level—by going directly to the brain. You think it, and the Muse headband will make it happen under very limited circumstances.

Visual Data Mining of Biological Networks: One Size Does Not Fit All

http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002833

High-throughput technologies produce massive amounts of data. However, individual methods yield data specific to the technique used and biological setup. The integration of such diverse data is necessary for the qualitative analysis of information relevant to hypotheses or discoveries. It is often useful to integrate these datasets using pathways and protein interaction networks to get a broader view of the experiment. The resulting network needs to be able to focus on either the large-scale picture or on the more detailed small-scale subsets, depending on the research question and goals. In this tutorial, we illustrate a workflow useful to integrate, analyze, and visualize data from different sources, and highlight important features of tools to support such analyses.

Web 3D

 jQuery, 

http://jquery.com/



Three.js,  (Javascript 3D Library)

https://github.com/mrdoob/three.js/



 OpenCTM (Compression of 3D Triangle Meshes).

 http://openctm.sourceforge.net/



http://gallantlab.org/semanticmovies/

Reconstructing visual experiences from brain activity evoked by natural movies

http://gallantlab.org/publications/nishimoto-et-al-2011.html


Shinji Nishimoto, An T. Vu, Thomas Naselaris, Yuval Benjamini, Bin Yu & Jack L. Gallant.
Current Biology, published online September 22, 2011.

Quantitative modeling of human brain activity can provide crucial insights about cortical representations and can form the basis for brain decoding devices. Recent functional magnetic resonance imaging (fMRI) studies have modeled brain activity elicited by static visual patterns and have reconstructed these patterns from brain activity. However, blood oxygen level-dependent (BOLD) signals measured via fMRI are very slow, so it has been difficult to model brain activity elicited by dynamic stimuli such as natural movies. Here we present a new motion-energy encoding model that largely overcomes this limitation. The model describes fast visual information and slow hemodynamics by separate components. We recorded BOLD signals in occipitotemporal visual cortex of human subjects who watched natural movies and fit the model separately to individual voxels. Visualization of the fit models reveals how early visual areas represent the information in movies. To demonstrate the power of our approach, we also constructed a Bayesian decoder by combining estimated encoding models with a sampled natural movie prior. The decoder provides remarkable reconstructions of the viewed movies. These results demonstrate that dynamic brain activity measured under naturalistic conditions can be decoded using current fMRI technology.

Introduction to Translational Bioinformatics Collection

http://www.ploscollections.org/downloads/TranslationalBioinformatics.pdf

Editorial

Ten Simple Rules for the Open Development of Scientific Software
Andreas Prlić, James B. Procter

Education

Introduction to Translational Bioinformatics Collection
Russ B. Altman

Chapter 1: Biomedical Knowledge Integration
Philip R. O. Payne

Chapter 2: Data-Driven View of Disease Biology
Casey S. Greene, Olga G. Troyanskaya

Chapter 3: Small Molecules and Disease
David S. Wishart

Chapter 4: Protein Interactions and Disease
Mileidy W. Gonzalez, Maricel G. Kann

Chapter 5: Network Biology Approach to Complex Diseases
Dong-Yeon Cho, Yoo-Ah Kim, Teresa M. Przytycka

Chapter 6: Structural Variation and Medical Genomics
Benjamin J. Raphael

Chapter 7: Pharmacogenomics
Konrad J. Karczewski, Roxana Daneshjou, Russ B. Altman

Chapter 8: Biological Knowledge Assembly and Interpretation
Ju Han Kim

Chapter 9: Analyses Using Disease Ontologies
Nigam H. Shah, Tyler Cole, Mark A. Musen

Chapter 10: Mining Genome-Wide Genetic Markers
Xiang Zhang, Shunping Huang, Zhaojun Zhang, Wei Wang

Chapter 11: Genome-Wide Association Studies
William S. Bush, Jason H. Moore

Chapter 12: Human Microbiome Analysis
Xochitl C. Morgan, Curtis Huttenhower

Chapter 13: Mining Electronic Health Records in the Genomics Era
Joshua C. Denny

Chapter 14: Cancer Genome Analysis
Miguel Vazquez, Victor de la Torre, Alfonso Valencia

Teaching the Fundamentals of Biological Data Integration Using Classroom Games
Maria Victoria Schneider, Rafael C. Jimenez

THE FIRST MAP OF HOW OUR BRAIN ORGANIZES EVERYTHING WE SEE

http://neurorelays.wordpress.com/2012/12/27/the-first-map-of-how-our-brain-organizes-everything-we-see/

A research published in the Cell Press journal Neuron on the 20th of December 2012 (Alexander G. Huth, Shinji Nishimoto, An T. Vu, Jack L. Gallant. A Continuous Semantic Space Describes the Representation of Thousands of Object and Action Categories across the Human Brain. Neuron, 2012; 76 (6): 1210 DOI:10.1016/j.neuron.2012.10.014) describes the first developed map of how our brain sorts everything we see.

IIPImage

http://iipimage.sourceforge.net/ 
 
IIPImage is an advanced high-performance feature-rich image server system for web-based streamed viewing and zooming of ultra high-resolution images. It is designed to be fast and bandwidth-efficient with low processor and memory requirements. The system can comfortably handle gigapixel size images as well as advanced image features such as both 8 and 16 bit depths, CIELAB colorimetric images and scientific imagery such as multispectral images.