References of "Valencia, A."
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See detailCOVID-19 Disease Map, building a computational repository of SARS-CoV-2 virus-host interaction mechanisms.
Ostaszewski, Marek UL; Mazein, Alexander UL; Gillespie, ME et al

in Scientific Data (2020)

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See detailPDBe-KB: a community-driven resource for structural and functional annotations
Varadi, M.; Berrisford, J.; Deshpande, M. et al

in Nucleic Acids Research (2019)

The Protein Data Bank in Europe-Knowledge Base (PDBe-KB, https://pdbe-kb.org) is a community-driven, collaborative resource for literature-derived, manually curated and computationally predicted ... [more ▼]

The Protein Data Bank in Europe-Knowledge Base (PDBe-KB, https://pdbe-kb.org) is a community-driven, collaborative resource for literature-derived, manually curated and computationally predicted structural and functional annotations of macromolecular structure data, contained in the Protein Data Bank (PDB). The goal of PDBe-KB is two-fold: (i) to increase the visibility and reduce the fragmentation of annotations contributed by specialist data resources, and to make these data more findable, accessible, interoperable and reusable (FAIR) and (ii) to place macromolecular structure data in their biological context, thus facilitating their use by the broader scientific community in fundamental and applied research. Here, we describe the guidelines of this collaborative effort, the current status of contributed data, and the PDBe-KB infrastructure, which includes the data exchange format, the deposition system for added value annotations, the distributable database containing the assembled data, and programmatic access endpoints. We also describe a series of novel web-pages—the PDBe-KB aggregated views of structure data—which combine information on macromolecular structures from many PDB entries. We have recently released the first set of pages in this series, which provide an overview of available structural and functional information for a protein of interest, referenced by a UniProtKB accession. [less ▲]

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See detailEnrichNet: network-based gene set enrichment analysis
Glaab, Enrico UL; Baudot, A.; Krasnogor, N. et al

in Bioinformatics (2012), 28(18), 451-457

Assessing functional associations between an experimentally derived gene or protein set of interest and a database of known gene/protein sets is a common task in the analysis of large-scale functional ... [more ▼]

Assessing functional associations between an experimentally derived gene or protein set of interest and a database of known gene/protein sets is a common task in the analysis of large-scale functional genomics data. For this purpose, a frequently used approach is to apply an over-representation-based enrichment analysis. However, this approach has four drawbacks: (i) it can only score functional associations of overlapping gene/proteins sets; (ii) it disregards genes with missing annotations; (iii) it does not take into account the network structure of physical interactions between the gene/protein sets of interest and (iv) tissue-specific gene/protein set associations cannot be recognized. RESULTS: To address these limitations, we introduce an integrative analysis approach and web-application called EnrichNet. It combines a novel graph-based statistic with an interactive sub-network visualization to accomplish two complementary goals: improving the prioritization of putative functional gene/protein set associations by exploiting information from molecular interaction networks and tissue-specific gene expression data and enabling a direct biological interpretation of the results. By using the approach to analyse sets of genes with known involvement in human diseases, new pathway associations are identified, reflecting a dense sub-network of interactions between their corresponding proteins. [less ▲]

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See detailSequence analysis of the Methanococcus jannaschii genome and the prediction of protein function
Andrade, M.; Casari, G.; deDaruvar, A. et al

in Computer Applications in the Biosciences [=CABIOS] (1997), 13(4), 481-483

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See detailCHALLENGING TIMES FOR BIOINFORMATICS
CASARI, G.; ANDRADE, M. A.; BORK, P. et al

in Nature (1995), 376(6542), 647-648

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See detailGeneQuiz: a workbench for sequence analysis
Scharf, M.; Schneider, Reinhard UL; Casari, G. et al

in Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology, ISMB-94 (1994)

We present the prototype of a software system, called GeneQuiz, for large-scale biological sequence analysis. The system was designed to meet the needs that arise in computational sequence analysis and ... [more ▼]

We present the prototype of a software system, called GeneQuiz, for large-scale biological sequence analysis. The system was designed to meet the needs that arise in computational sequence analysis and our past experience with the analysis of 171 protein sequences of yeast chromosome III. We explain the cognitive challenges associated with this particular research activity and present our model of the sequence analysis process. The prototype system consists of two parts: (i) the database update and search system (driven by perl programs and rdb, a simple relational database engine also written in perl) and (ii) the visualization and browsing system (developed under C++/ET++). The principal design requirement for the first part was the complete automation of all repetitive actions: database updates, efficient sequence similarity searches and sampling of results in a uniform fashion. The user is then presented with "hit-lists" that summarize the results from heterogeneous database searches. The expert's primary task now simply becomes the further analysis of the candidate entries, where the problem is to extract adequate information about functional characteristics of the query protein rapidly. This second task is tremendously accelerated by a simple combination of the heterogeneous output into uniform relational tables and the provision of browsing mechanisms that give access to database records, sequence entries and alignment views. Indexing of molecular sequence databases provides fast retrieval of individual entries with the use of unique identifiers as well as browsing through databases using pre-existing cross-references. The presentation here covers an overview of the architecture of the system prototype and our experiences on its applicability in sequence analysis. [less ▲]

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See detailCorrelated mutations and residue contacts in proteins
Göbel, U.; Sander, C.; Schneider, Reinhard UL et al

in Proteins (1994), 18

The maintenance of protein function and structure constrains the evolution of amino acid sequences. This fact can be exploited to interpret correlated mutations observed in a sequence family as an ... [more ▼]

The maintenance of protein function and structure constrains the evolution of amino acid sequences. This fact can be exploited to interpret correlated mutations observed in a sequence family as an indication of probable physical contact in three dimensions. Here we present a simple and general method to analyze correlations in mutational behavior between different positions in a multiple sequence alignment. We then use these correlations to predict contact maps for each of 11 protein families and compare the result with the contacts determined by crystallography. For the most strongly correlated residue pairs predicted to be in contact, the prediction accuracy ranges from 37 to 68% and the improvement ratio relative to a random prediction from 1.4 to 5.1. Predicted contact maps can be used as input for the calculation of protein tertiary structure, either from sequence information alone or in combination with experimental information. [less ▲]

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