A5051257421- Genomics and Phylogenetic Studies
- Genomics and Rare Diseases
- Bioinformatics and Genomic Networks
- Machine Learning in Bioinformatics
- RNA and protein synthesis mechanisms
- Microbial Metabolic Engineering and Bioproduction
- Biomedical Text Mining and Ontologies
- Evolution and Genetic Dynamics
- Computational Drug Discovery Methods
- Protein Structure and Dynamics
- Mitochondrial Function and Pathology
- Microbial Natural Products and Biosynthesis
- Gene expression and cancer classification
Technical University of Munich
2013-2017
Automated annotation of protein function is challenging. As the number sequenced genomes rapidly grows, overwhelming majority products can only be annotated computationally. If computational predictions are to relied upon, it crucial that accuracy these methods high. Here we report results from first large-scale community-based critical assessment (CAFA) experiment. Fifty-four representing state art for prediction were evaluated on a target set 866 proteins 11 organisms. Two findings stand...
Elucidating the effects of naturally occurring genetic variation is one major challenges for personalized health and medicine. Here, we introduce SNAP2, a novel neural network based classifier that improves over state-of-the-art in distinguishing between effect neutral variants. Our method's improved performance results from screening many potentially relevant protein features refining our development data sets. Cross-validated on >100k experimentally annotated variants, SNAP2 significantly...
PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with protein it returns: multiple alignments, predicted aspects structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) strands, coiled-coil regions, disulfide bonds disordered regions) function. The service incorporates methods the identification regions (ConSurf), homology-based inference Gene Ontology terms...
The prediction of protein sub-cellular localization is an important step toward elucidating function. For each query sequence, LocTree2 applies machine learning (profile kernel SVM) to predict the native in 18 classes for eukaryotes, six bacteria and three archaea. method outputs a score that reflects reliability prediction. has performed on par with or better than any other state-of-the-art method. Here, we report availability LocTree3 as public web server. server includes learning-based...
Any method that de novo predicts protein function should do better than random. More challenging, it also ought to outperform simple homology-based inference.Here, we describe a few methods predict exclusively through homology. Together, they set the bar or lower limit for future improvements.During development of these methods, faced two surprises. Firstly, our most successful implementation baseline ranked very high at CAFA1. In fact, best combination fared only slightly worse...
Any two unrelated individuals differ by about 10,000 single amino acid variants (SAVs). Do these impact molecular function? Experimental answers cannot answer comprehensively, while state-of-the-art prediction methods can. We predicted the functional impacts of SAVs within human and for between other species. Several surprising results stood out. Firstly, four (CADD, PolyPhen-2, SIFT, SNAP2) agreed 10 percentage points on rare with effect. However, they differed substantially common SAVs:...
<ns4:p><ns4:bold>Summary: </ns4:bold>The HeatMapViewer is a BioJS component that lays-out and renders two-dimensional (2D) plots or heat maps are ideally suited to visualize matrix formatted data in biology such as for the display of microarray experiments outcome mutational studies study SNP-like sequence variants. It can be easily integrated into documents provides powerful, interactive way web applications. The software uses scalable graphics technology adapts visualization any required...
Developments in experimental and computational biology are advancing our understanding of how protein sequence variation impacts molecular function. However, the leap from micro level function to macro whole organism, e.g. disease, remains barred. Here, we present new results emphasizing earlier work that suggested some links disease. We focused on non-synonymous single nucleotide variants, also referred as amino acid variants (SAVs). Building upon OMIA (Online Mendelian Inheritance...