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Sequencing datasets consist of a finite number of reads which map to specific regions of a reference genome. Most effort in modeling these datasets focuses on the detection of univariate differentially express...
Popular bioinformatics approaches for studying protein functional dynamics include comparisons of crystallographic structures, molecular dynamics simulations and normal mode analysis. However, determining how ...
Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of ‘omics’ data can be...
Our knowledge of global protein-protein interaction (PPI) networks in complex organisms such as humans is hindered by technical limitations of current methods.
Metabolomics is one of most recent omics technologies. It has been applied on fields such as food science, nutrition, drug discovery and systems biology. For this, gas chromatography-mass spectrometry (GC-MS) ...
Drug-induced nephrotoxicity causes acute kidney injury and chronic kidney diseases, and is a major reason for late-stage failures in the clinical trials of new drugs. Therefore, early, pre-clinical prediction ...
Bioinformatics software quality assurance is essential in genomic medicine. Systematic verification and validation of bioinformatics software is difficult because it is often not possible to obtain a realistic...
Cophylogeny mapping is used to uncover deep coevolutionary associations between two or more phylogenetic histories at a macro coevolutionary scale. As cophylogeny mapping is NP-Hard, this technique relies heav...
Interaction of the small peptide hormone glucagon with glucagon receptor (GCGR) stimulates the release of glucose from the hepatic cells during fasting; hence GCGR performs a significant function in glucose ho...
Deciphering three dimensional structure of a protein sequence is a challenging task in biological science. Protein fold recognition and protein secondary structure prediction are transitional steps in identify...
Assessment of risk and early diagnosis of Alzheimer's disease (AD) is a key to its prevention or slowing the progression of the disease. Previous research on risk factors for AD typically utilizes statistical ...
Comprehensive characterization of the phosphoproteome in living cells is critical in signal transduction research. But the low abundance of phosphopeptides among the total proteome in cells remains an obstacle...
Protein-protein docking is an in silico method to predict the formation of protein complexes. Due to limited computational resources, the protein-protein docking approach has been developed under the assumption o...
Protein chains are generally long and consist of multiple domains. Domains are distinct structural units of a protein that can evolve and function independently. The accurate prediction of protein domain linke...
The advent of human genome sequencing project has led to a spurt in the number of protein sequences in the databanks. Success of structure based drug discovery severely hinges on the availability of structures...
During metamorphosis in Drosophila melanogaster, larval muscles undergo two different developmental fates; one population is removed by cell death, while the other persistent subset undergoes morphological remode...
A pharmacophore model consists of a group of chemical features arranged in three-dimensional space that can be used to represent the biological activities of the described molecules. Clustering of molecular in...
Heme binding proteins (HBPs) are metalloproteins that contain a heme ligand (an iron-porphyrin complex) as the prosthetic group. Several computational methods have been proposed to predict heme binding residue...
Distinction between true protein interactions and crystal packing contacts is important for structural bioinformatics studies to respond to the need of accurate classification of the rapidly increasing protein...
In practice, some drugs produce a number of negative biological effects that can mitigate their effectiveness as a remedy. To address this issue, several studies have been performed for the prediction of drug-...
Protein O-GlcNAcylation, involving the attachment of single N-acetylglucosamine (GlcNAc) to the hydroxyl group of serine or threonine residues. Elucidation of O-GlcNAcylation sites on proteins is required in orde...
Since 2006, the International Conference on Bioinformatics (InCoB) has been publishing selected papers in BMC Bioinformatics. Papers within the scope of the journal from the 13th InCoB July 31-2 August, 2014 i...
Over the last few years transcriptome sequencing (RNA-Seq) has almost completely taken over microarrays for high-throughput studies of gene expression. Currently, the most popular use of RNA-Seq is to identify...
Applying machine learning methods on microarray gene expression profiles for disease classification problems is a popular method to derive biomarkers, i.e. sets of genes that can predict disease state or outco...
Within many research areas, such as transcriptomics, the millions of short DNA fragments (reads) produced by current sequencing platforms need to be assembled into transcript sequences before they can be utili...
The exponential growth of next-generation sequencing (NGS) derived DNA data poses great challenges to data storage and transmission. Although many compression algorithms have been proposed for DNA reads in NGS...
Identifying protein-protein interactions (PPIs) is essential for elucidating protein functions and understanding the molecular mechanisms inside the cell. However, the experimental methods for detecting PPIs a...
To infer gene regulatory networks from time series gene profiles, two important tasks that are related to biological systems must be undertaken. One task is to determine a valid network structure that has topo...
Expressed sequences (e.g. ESTs) are a strong source of evidence to improve gene structures and predict reliable alternative splicing events. When a genome assembly is available, ESTs are suitable to generate g...
Measuring protein structural similarity attempts to establish a relationship of equivalence between polymer structures based on their conformations. In several recent studies, researchers have explored protein...
Interaction of proteins with other molecules plays an important role in many biological activities. As many structures of protein-DNA complexes and protein-RNA complexes have been determined in the past years,...
Protein-ligand binding is important for some proteins to perform their functions. Protein-ligand binding sites are the residues of proteins that physically bind to ligands. Despite of the recent advances in co...
Differential coexpression analysis usually requires the definition of 'distance' or 'similarity' between measured datasets. Until now, the most common choice is Pearson correlation coefficient. However, Pearso...
Previous studies have demonstrated that machine learning based molecular cancer classification using gene expression profiling (GEP) data is promising for the clinic diagnosis and treatment of cancer. Novel cl...
Protein folding structure prediction is one of the most challenging problems in the bioinformatics domain. Because of the complexity of the realistic protein structure, the simplified structure model and the c...
Predication of gene regularity network (GRN) from expression data is a challenging task. There are many methods that have been developed to address this challenge ranging from supervised to unsupervised method...
The invasion of red blood cells (RBCs) by malarial parasites is an essential step in the life cycle of Plasmodium falciparum. Human-parasite surface protein interactions play a critical role in this process. Alth...
The identification of new diagnostic or prognostic biomarkers is one of the main aims of clinical cancer research. Technologies like mass spectrometry are commonly being used in proteomic research. Mass spectr...
In order to extract meaningful information from electronic medical records, such as signs and symptoms, diagnoses, and treatments, it is important to take into account the contextual properties of the identifi...
Increasing number of eQTL (Expression Quantitative Trait Loci) datasets facilitate genetics and systems biology research. Meta-analysis tools are in need to jointly analyze datasets of same or similar issue ty...
Next generation sequencing technology has allowed efficient production of draft genomes for many organisms of interest. However, most draft genomes are just collections of independent contigs, whose relative p...
The growing wealth of public available gene expression data has made the systemic studies of how genes interact in a cell become more feasible. Liquid association (LA) describes the extent to which coexpressio...
Post-translational modifications (PTMs) constitute a major aspect of protein biology, particularly signaling events. Conversely, several different pathophysiological PTMs are hallmarks of oxidative imbalance o...
Computational expression deconvolution aims to estimate the contribution of individual cell populations to expression profiles measured in samples of heterogeneous composition. Zhong et al. recently proposed D...
Computational biology comprises a wide range of technologies and approaches. Multiple technologies can be combined to create more powerful workflows if the individuals contributing the data or providing tools ...
Text mining services are rapidly becoming a crucial component of various knowledge management pipelines, for example in the process of database curation, or for exploration and enrichment of biomedical data wi...
Reporting and sharing experimental metadata- such as the experimental design, characteristics of the samples, and procedures applied, along with the analysis results, in a standardised manner ensures that data...
Life-science laboratories make increasing use of Next Generation Sequencing (NGS) for studying bio-macromolecules and their interactions. Array-based methods for measuring gene expression or protein-DNA intera...
Computing semantic relatedness between textual labels representing biological and medical concepts is a crucial task in many automated knowledge extraction and processing applications relevant to the biomedica...
The thirteenth NETTAB workshop, NETTAB 2013, was devoted to semantic, social, and mobile applications for bioinformatics and biomedical laboratories.
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