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Friday, September 26, 2014

Computer method IMPACT-F replaces unreliable animal tests

Experiments in animals are used to estimate drug-uptake in humans. If drug-uptake in animals is too low, drug candidates are excluded from further development.

But large differences exist on drug-uptake between animals and humans. This also applies to very successful commercial drugs, called blockbuster drugs, with annual sales of more than one billion US Dollar.

Drug-uptake studies in animals are misleading: Aripiprazole and Esomeprazole, the most sold drugs of 2013, have low oral bioavailability in animals, but drug-uptake in humans is high.

The new expert system IMPACT-F replaces animal trials on drug-uptake.

Pharmaceutical companies have applied the expert system to evaluate human drug-uptake in various therapeutic areas such as diabetes, inflammation, antivirals, autoimmune diseases and cancer.

The expert system evaluates drug-uptake in humans significantly more reliably than animal trials. This further increases the prospects of human clinical trials, because the optimum oral dose for first-in-human clinical trials can be determined much more accurately.

Efficacy issues are identified as the main reason why clinical trials fail.

About PharmaInformatic:
The biotech company PharmaInformatic was founded in 2004 and provides ADME knowledge bases and predictive tools (expert systems) to improve drug discovery and development. The company is based in Germany.
www.pharmainformatic.com


Further detailed information:
http://www.pharmainformatic.com/html/partnerships.html

http://www.pharmainformatic.com/html/blockbuster_drugs.html

URL: http://www.pharmainformatic.com

Contact Person: Dr. Wolfgang Boomgaarden (presse@pharmainformatic.com)

Friday, September 19, 2014

Extended deadline Special Issue: Advances in Computational Methods for Genetic Diseases

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CFP
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Special Issue - Advances in Computational Methods for Genetic Diseases - Computational and Mathematical Methods in Medicine, Hindawi

Due to potential authors requests, the deadline for the submission of papers has been extended. The new Issue schedule is the following:

_________________
IMPORTANT DATES
_________________

Manuscript Due Friday, 19 OCTOBER 2014
First Round of Reviews Friday, 12 December 2014
Publication Date Friday, 6 February 2015

_________________
CALL FOR PAPERS
_________________

Genetic diseases are widely studied for the relevant impact on the human health. In the last years, a large amount of experimental data has been available. The identification of new strategies for elaborating such experimental data is becoming more and more necessary since the large amount of information can sometimes represent a real obstacle for the effective identification of relevant findings. The aim of the special issue is to review the recent advances about the research on computational methods concerning with genetic diseases. Potential topics include, but are not limited to:

Computational and mathematical methods for the following:
- Evaluating the pathogenicity of novel genetic variants
- The evaluation of protein folding and/or protein-protein interactions in presence of genetic variants
- Analysis of experimental data from next generation sequencing
- Searching for variant/mutation databases for massive data analysis
- Analysis of "omics" data
- Analysis of complex diseases, namely, multifactorial and polygenic, for example, diabetes, hypertension and dyslipidemia
- Variant analysis from Genome Wide Association studies
- Analysis of common genetic variants (i.e., SNPs, HLA genotypes, microsatellites)
- Analysis of quantitative trait loci
- The integration of genetic and non genetic factors for prediction of disease predisposition
- The identification of potential gene regulatory elements (i.e., binding of transcription factors, and miRNAs)
- Analysis of gene expression data
- Analysis of biological models of genetic diseases

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/cmmm/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/cmmm/genet/

URL: http://www.hindawi.com/journals/cmmm/si/828505/cfp/

Contact Person: Antonino Staiano (antonino.staiano@uniparthenope.it)
URL: http://www.hindawi.com/journals/cmmm/osi/

Contact Person: Antonino Staiano (antonino.staiano@uniparthenope.it)

Tuesday, September 2, 2014

Last call for papers: Advances in Computational Methods for Genetic Diseases

******
CFP
******
Special Issue - Advances in Computational Methods for Genetic Diseases - Computational and Mathematical Methods in Medicine, Hindawi


_________________
IMPORTANT DATES
_________________

Manuscript Due Friday, 19 September 2014
First Round of Reviews Friday, 12 December 2014
Publication Date Friday, 6 February 2015

_________________
CALL FOR PAPERS
_________________


Genetic diseases are widely studied for the relevant impact on the human health. In the last years, a large amount of experimental data has been available. The identification of new strategies for elaborating such experimental data is becoming more and more necessary since the large amount of information can sometimes represent a real obstacle for the effective identification of relevant findings. The aim of the special issue is to review the recent advances about the research on computational methods concerning with genetic diseases. Potential topics include, but are not limited to:

Computational and mathematical methods for the following:
- Evaluating the pathogenicity of novel genetic variants
- The evaluation of protein folding and/or protein-protein interactions in presence of genetic variants
- Analysis of experimental data from next generation sequencing
- Searching for variant/mutation databases for massive data analysis
- Analysis of "omics" data
- Analysis of complex diseases, namely, multifactorial and polygenic, for example, diabetes, hypertension and dyslipidemia
- Variant analysis from Genome Wide Association studies
- Analysis of common genetic variants (i.e., SNPs, HLA genotypes, microsatellites)
- Analysis of quantitative trait loci
- The integration of genetic and non genetic factors for prediction of disease predisposition
- The identification of potential gene regulatory elements (i.e., binding of transcription factors, and miRNAs)
- Analysis of gene expression data
- Analysis of biological models of genetic diseases

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/cmmm/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/cmmm/genet/



URL: http://www.hindawi.com/journals/cmmm/si/828505/cfp/

Contact Person: Antonino Staiano (antonino.staiano@uniparthenope.it)
URL: http://www.hindawi.com/journals/cmmm/si/828505/cfp/

Contact Person: Antonino Staiano (antonino.staiano@uniparthenope.it)