SCOTCH: subtype A coreceptor tropism classification in HIV-1.

Motivation: The V3 loop of the gp120 glycoprotein of the Human Immunodeficiency Virus 1 (HIV-1) is considered to be responsible for viral coreceptor tropism. gp120 interacts with the CD4 receptor of the host cell and subsequently V3 binds either CCR5 or CXCR4. Due to the fact that the CCR5 coreceptor is targeted by entry inhibitors, a reliable prediction of the coreceptor usage of HIV-1 is of great interest for antiretroviral therapy.

eccCL: parallelized GPU implementation of Ensemble Classifier Chains.

Background: Multi-label classification has recently gained great attention in diverse fields of research, e.g., in biomedical application such as protein function prediction or drug resistance testing in HIV.

A systematic SNP selection approach to identify mechanisms underlying disease aetiology: linking height to post-menopausal breast and colorectal cancer risk.

Data from GWAS suggest that SNPs associated with complex diseases or traits tend to co-segregate in regions of low recombination, harbouring functionally linked gene clusters. This phenomenon allows for selecting a limited number of SNPs from GWAS repositories for large-scale studies investigating shared mechanisms between diseases. For example, we were interested in shared mechanisms between adult-attained height and post-menopausal breast cancer (BC) and colorectal cancer (CRC) risk, because height is a risk factor for these cancers, though likely not a causal factor.

Rare genetic variants in SMAP1, B3GAT2, and RIMS1 contribute to pediatric venous thromboembolism.

Recent genome-wide association studies (GWAS) have confirmed known risk mutations for venous thromboembolism (VTE) and identified a number of novel susceptibility loci in adults. Here we present a GWAS in 212 nuclear families with pediatric VTE followed by targeted next-generation sequencing (NGS) to identify causative mutations contributing to the association. Three single nucleotide polymorphisms (SNPs) exceeded the threshold for genome-wide significance as determined by permutation testing using 100 000 bootstrap permutations ( < 10).

Compensation of feature selection biases accompanied with improved predictive performance for binary classification by using a novel ensemble feature selection approach.

Motivation: Biomarker discovery methods are essential to identify a minimal subset of features (e.g., serum markers in predictive medicine) that are relevant to develop prediction models with high accuracy.

SHIVA - a web application for drug resistance and tropism testing in HIV.

Background: Drug resistance testing is mandatory in antiretroviral therapy in human immunodeficiency virus (HIV) infected patients for successful treatment. The emergence of resistances against antiretroviral agents remains the major obstacle in inhibition of viral replication and thus to control infection. Due to the high mutation rate the virus is able to adapt rapidly under drug pressure leading to the evolution of resistant variants and finally to therapy failure.

Genotypic Prediction of Co-receptor Tropism of HIV-1 Subtypes A and C.

Antiretroviral treatment of Human Immunodeficiency Virus type-1 (HIV-1) infections with CCR5-antagonists requires the co-receptor usage prediction of viral strains. Currently available tools are mostly designed based on subtype B strains and thus are in general not applicable to non-B subtypes. However, HIV-1 infections caused by subtype B only account for approximately 11% of infections worldwide.

Current Approaches in Computational Drug Resistance Prediction in HIV.

Background: Today a broad range of antiretroviral drug regimens are applicable for the successful suppression of virus replication in human immunodeficiency virus (HIV) infected people. However, there still remains an obstacle in therapy: the high mutation rate of the HI virus under drug pressure leads to resistant variants causing failure of permanent and effective treatment. Therefore, resistance testing is therefore inevitable to administer appropriate antiviral drugs to infected patients.

Exploiting HIV-1 protease and reverse transcriptase cross-resistance information for improved drug resistance prediction by means of multi-label classification.

Background: Antiretroviral therapy is essential for human immunodeficiency virus (HIV) infected patients to inhibit viral replication and therewith to slow progression of disease and prolong a patient's life. However, the high mutation rate of HIV can lead to a fast adaptation of the virus under drug pressure and thereby to the evolution of resistant variants. In turn, these variants will lead to the failure of antiretroviral treatment.

In Acute Myocardial Infarction Liver Parameters Are Associated With Stenosis Diameter.

Detection of high-risk subjects in acute myocardial infarction (AMI) by noninvasive means would reduce the need for intracardiac catheterization and associated complications. Liver enzymes are associated with cardiovascular disease risk. A potential predictive value for liver serum markers for the severity of stenosis in AMI was analyzed.

DNA methylation in an engineered heart tissue model of cardiac hypertrophy: common signatures and effects of DNA methylation inhibitors.

DNA methylation affects transcriptional regulation and constitutes a drug target in cancer biology. In cardiac hypertrophy, DNA methylation may control the fetal gene program. We therefore investigated DNA methylation signatures and their dynamics in an in vitro model of cardiac hypertrophy based on engineered heart tissue (EHT).

Fetal-adult cardiac transcriptome analysis in rats with contrasting left ventricular mass reveals new candidates for cardiac hypertrophy.

Reactivation of fetal gene expression patterns has been implicated in common cardiac diseases in adult life including left ventricular (LV) hypertrophy (LVH) in arterial hypertension. Thus, increased wall stress and neurohumoral activation are discussed to induce the return to expression of fetal genes after birth in LVH. We therefore aimed to identify novel potential candidates for LVH by analyzing fetal-adult cardiac gene expression in a genetic rat model of hypertension, i.

Transcriptome assessment reveals a dominant role for TLR4 in the activation of human monocytes by the alarmin MRP8.

The alarmins myeloid-related protein (MRP)8 and MRP14 are the most prevalent cytoplasmic proteins in phagocytes. When released from activated or necrotic phagocytes, extracellular MRP8/MRP14 promote inflammation in many diseases, including infections, allergies, autoimmune diseases, rheumatoid arthritis, and inflammatory bowel disease. The involvement of TLR4 and the multiligand receptor for advanced glycation end products as receptors during MRP8-mediated effects on inflammation remains controversial.

MANIA-a pattern classification toolbox for neuroimaging data.

Conventional univariate statistics are common and widespread in neuroimaging research. However, functional and structural MRI data reveal a multivariate nature, since neighboring voxels are highly correlated and different localized brain regions activate interdependently. Multivariate pattern classification techniques are capable of overcoming shortcomings of univariate statistics.

Evolutionary dynamics of co-segregating gene clusters associated with complex diseases.

Background: The distribution of human disease-associated mutations is not random across the human genome. Despite the fact that natural selection continually removes disease-associated mutations, an enrichment of these variants can be observed in regions of low recombination. There are a number of mechanisms by which such a clustering could occur, including genetic perturbations or demographic effects within different populations.

Improved Bevirimat resistance prediction by combination of structural and sequence-based classifiers.

Background: Maturation inhibitors such as Bevirimat are a new class of antiretroviral drugs that hamper the cleavage of HIV-1 proteins into their functional active forms. They bind to these preproteins and inhibit their cleavage by the HIV-1 protease, resulting in non-functional virus particles. Nevertheless, there exist mutations in this region leading to resistance against Bevirimat.