SNP-SIG Meeting 2011: Identification and annotation of SNPs in the context of structure, function, and disease
Citation:
BMC Genomics
2012
13(Suppl 4):S1
Volume 13 Supplement 4
SNP-SIG 2011: Identification and annotation of SNPs in the context of structure, function and disease
Proceedings
Edited by Yana Bromberg and Emidio Capriotti
SNP-SIG 2011: Identification and annotation of SNPs in the context of structure, function and disease. Go to conference site.
Vienna, Austria15 July 2011
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How to evaluate performance of prediction methods? Measures and their interpretation in variation effect analysis
Prediction methods are increasingly used in biosciences to forecast diverse features and characteristics. Binary two-state classifiers are the most common applications. They are usually based on machine learni...
Citation: BMC Genomics 2012 13(Suppl 4):S2 -
Prioritization of pathogenic mutations in the protein kinase superfamily
Most of the many mutations described in human protein kinases are tolerated without significant disruption of the corresponding structures or molecular functions, while some of them have been associated to a v...
Citation: BMC Genomics 2012 13(Suppl 4):S3 -
Predict impact of single amino acid change upon protein structure
Amino acid point mutations (nsSNPs) may change protein structure and function. However, no method directly predicts the impact of mutations on structure. Here, we compare pairs of pentamers (five consecutive r...
Citation: BMC Genomics 2012 13(Suppl 4):S4 -
On the effect of protein conformation diversity in discriminating among neutral and disease related single amino acid substitutions
Non-synonymous coding SNPs (nsSNPs) that are associated to disease can also be related with alterations in protein stability. Computational methods are available to predict the effect of single amino acid subs...
Citation: BMC Genomics 2012 13(Suppl 4):S5 -
Evaluating our ability to predict the structural disruption of RNA by SNPs
The structure of RiboNucleic Acid (RNA) has the potential to be altered by a Single Nucleotide Polymorphism (SNP). Disease-associated SNPs mapping to non-coding regions of the genome that are transcribed into ...
Citation: BMC Genomics 2012 13(Suppl 4):S6 -
Large-scale computational identification of regulatory SNPs with rSNP-MAPPER
The computational analysis of regulatory SNPs (rSNPs) is an essential step in the elucidation of the structure and function of regulatory networks at the cellular level. In this work we focus in particular on ...
Citation: BMC Genomics 2012 13(Suppl 4):S7 -
Predicting cancer-associated germline variations in proteins
Various computational methods are presently available to classify whether a protein variation is disease-associated or not. However data derived from recent technological advancements make it feasible to exten...
Citation: BMC Genomics 2012 13(Suppl 4):S8 -
Domain landscapes of somatic mutations in cancer
Large-scale tumor sequencing projects are now underway to identify genetic mutations that drive tumor initiation and development. Most studies take a gene-based approach to identifying driver mutations, highli...
Citation: BMC Genomics 2012 13(Suppl 4):S9 -
Automated extraction and semantic analysis of mutation impacts from the biomedical literature
Mutations as sources of evolution have long been the focus of attention in the biomedical literature. Accessing the mutational information and their impacts on protein properties facilitates research in variou...
Citation: BMC Genomics 2012 13(Suppl 4):S10 -
Disease-related mutations predicted to impact protein function
Non-synonymous single nucleotide polymorphisms (nsSNPs) alter the protein sequence and can cause disease. The impact has been described by reliable experiments for relatively few mutations. Here, we study pred...
Citation: BMC Genomics 2012 13(Suppl 4):S11
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