Bioinformatics Researcher
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Rescooped by BENM FENG from Autoimmune diseases (Lupus, RA), Vaccines and Stem Cell Therapies Highlights
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Cell imaging: Beyond the limits : Nature : Nature Publishing Group

Cell imaging: Beyond the limits : Nature : Nature Publishing Group | Bioinformatics Researcher | Scoop.it
Powerful super-resolution microscopes that allow researchers to explore the world at the nanoscale are set to transform our understanding of the cell.

Via Krishan Maggon
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Krishan Maggon 's curator insight, October 22, 2015 9:50 AM

NATURE | OUTLOOK 

Cell imaging: Beyond the limitsKatherine BourzacNature 526, S50–S54 (22 October 2015) doi:10.1038/526S50aPublished online 21 October 2015
Rescooped by BENM FENG from Bioinformatics Software: Sequence Analysis
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Allele-specific RNA-seq pipeline using Gsnap and GATK


Via Mel Melendrez-Vallard
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Rescooped by BENM FENG from Bioinformatics, Comparative Genomics and Molecular Evolution
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Beyond Silicon: The Evolution of Biological Computing | Triple Helix Online

Beyond Silicon: The Evolution of Biological Computing | Triple Helix Online | Bioinformatics Researcher | Scoop.it
In 1965, Gordon Moore predicted that processing power should double every eighteen months.1 Traditionally, this rapid growth has been achieved by shrinking

Via Arjen ten Have
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Rescooped by BENM FENG from Bioinformatics Software: Sequence Analysis
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MITIE: Simultaneous RNA-Seq-based Transcript Identification and Quantification in Multiple Samples

High throughput sequencing of mRNA (RNA-Seq) has led to tremendous improvements in the detection of expressed genes and reconstruction of RNA transcripts.

Via Mel Melendrez-Vallard
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Rescooped by BENM FENG from Viruses and Bioinformatics from Virology.uvic.ca
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Assembler for de novo assembly of large genomes


Via Chris Upton + helpers
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Rescooped by BENM FENG from Plant Genomics
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DNA-free genome editing in plants with preassembled CRISPR-Cas9 ribonucleoproteins

DNA-free genome editing in plants with preassembled CRISPR-Cas9 ribonucleoproteins | Bioinformatics Researcher | Scoop.it
Editing plant genomes without introducing foreign DNA into cells may alleviate regulatory concerns related to genetically modified plants. We transfected preassembled complexes of purified Cas9 protein and guide RNA into plant protoplasts of Arabidopsis thaliana, tobacco, lettuce and rice and achieved targeted mutagenesis in regenerated plants at frequencies of up to 46%. The targeted sites contained germline-transmissible small insertions or deletions that are indistinguishable from naturally occurring genetic variation.

Via Biswapriya Biswavas Misra
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Biswapriya Biswavas Misra's curator insight, November 5, 2015 9:45 PM

Editing plant genomes without introducing foreign DNA into cells may alleviate regulatory concerns related to genetically modified plants. We transfected preassembled complexes of purified Cas9 protein and guide RNA into plant protoplasts of Arabidopsis thaliana, tobacco, lettuce and rice and achieved targeted mutagenesis in regenerated plants at frequencies of up to 46%. The targeted sites contained germline-transmissible small insertions or deletions that are indistinguishable from naturally occurring genetic variation.

Rescooped by BENM FENG from Bioinformatics Software: Sequence Analysis
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Count-based differential expression analysis of RNA sequencing data using R and Bioconductor | RNA-Seq Blog

Count-based differential expression analysis of RNA sequencing data using R and Bioconductor | RNA-Seq Blog | Bioinformatics Researcher | Scoop.it
RNA sequencing (RNA-seq) has been rapidly adopted for the profiling of transcriptomes in many areas of biology, including studies into gene regulation, (Count-based differential expression analysis of #RNA sequencing data using R and...

Via Mel Melendrez-Vallard
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Rescooped by BENM FENG from Systems biology and bioinformatics
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Network deconvolution as a general method to distinguish direct dependencies in networks

Network deconvolution as a general method to distinguish direct dependencies in networks | Bioinformatics Researcher | Scoop.it

Recognizing direct relationships between variables connected in a network is a pervasive problem in biological, social and information sciences as correlation-based networks contain numerous indirect relationships. Here we present a general method for inferring direct effects from an observed correlation matrix containing both direct and indirect effects. We formulate the problem as the inverse of network convolution, and introduce an algorithm that removes the combined effect of all indirect paths of arbitrary length in a closed-form solution by exploiting eigen-decomposition and infinite-series sums. We demonstrate the effectiveness of our approach in several network applications: distinguishing direct targets in gene expression regulatory networks; recognizing directly interacting amino-acid residues for protein structure prediction from sequence alignments; and distinguishing strong collaborations in co-authorship social networks using connectivity information alone. In addition to its theoretical impact as a foundational graph theoretic tool, our results suggest network deconvolution is widely applicable for computing direct dependencies in network science across diverse disciplines.

 

Network deconvolution as a general method to distinguish direct dependencies in networks
Soheil Feizi, Daniel Marbach, Muriel Médard & Manolis Kellis

Nature Biotechnology 31, 726–733 (2013) http://dx.doi.org/10.1038/nbt.2635


Via Complexity Digest, Dmitry Alexeev
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Dmitry Alexeev's curator insight, August 13, 2013 12:30 AM

complexity is paving the way - now we look for directed graph

 

Rescooped by BENM FENG from Amazing Science
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Amazing Science: Bioinformatics Postings

Amazing Science: Bioinformatics Postings | Bioinformatics Researcher | Scoop.it

Bioinformatics is an interdisciplinary field that develops and improves upon methods for storing, retrieving, organizing and analyzing biological data. A major activity in bioinformatics is to develop software tools to generate useful biological knowledge. Bioinformatics has become an important part of many areas of biology. In experimental molecular biology, bioinformatics techniques such as image and signal processing allow extraction of useful results from large amounts of raw data. In the field of genetics and genomics, it aids in annotating genomes and their observed mutations.


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Rescooped by BENM FENG from Plant Genomics
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De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis

De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis | Bioinformatics Researcher | Scoop.it

Via Biswapriya Biswavas Misra
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Biswapriya Biswavas Misra's curator insight, July 25, 2013 5:42 PM

De novo assembly of RNA-seq data enables researchers to study transcriptomes without the need for a genome sequence; this approach can be usefully applied, for instance, in research on 'non-model organisms' of ecological and evolutionary importance, cancer samples or the microbiome. In this protocol we describe the use of the Trinity platform for de novo transcriptome assembly from RNA-seq data in non-model organisms. We also present Trinity-supported companion utilities for downstream applications, including RSEM for transcript abundance estimation, R/Bioconductor packages for identifying differentially expressed transcripts across samples and approaches to identify protein-coding genes. In the procedure, we provide a workflow for genome-independent transcriptome analysis leveraging the Trinity platform. The software, documentation and demonstrations are freely available from http://trinityrnaseq.sourceforge.net. The run time of this protocol is highly dependent on the size and complexity of data to be analyzed. The example data set analyzed in the procedure detailed herein can be processed in less than 5 h.