1,720,985 research outputs found

    PhenPath: A tool for characterizing biological functions underlying different phenotypes

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    Background Many diseases are associated with complex patterns of symptoms and phenotypic manifestations. Parsimonious explanations aim at reconciling the multiplicity of phenotypic traits with the perturbation of one or few biological functions. For this, it is necessary to characterize human phenotypes at the molecular and functional levels, by exploiting gene annotations and known relations among genes, diseases and phenotypes. This characterization makes it possible to implement tools for retrieving functions shared among phenotypes, co-occurring in the same patient and facilitating the formulation of hypotheses about the molecular causes of the disease. Results We introduce PhenPath, a new resource consisting of two parts: PhenPathDB and PhenPathTOOL. The former is a database collecting the human genes associated with the phenotypes described in Human Phenotype Ontology (HPO) and OMIM Clinical Synopses. Phenotypes are then associated with biological functions and pathways by means of NET-GE, a network-based method for functional enrichment of sets of genes. The present version considers only phenotypes related to diseases. PhenPathDB collects information for 18 OMIM Clinical synopses and 7137 HPO phenotypes, related to 4292 diseases and 3446 genes. Enrichment of Gene Ontology annotations endows some 87.7, 86.9 and 73.6% of HPO phenotypes with Biological Process, Molecular Function and Cellular Component terms, respectively. Furthermore, 58.8 and 77.8% of HPO phenotypes are also enriched for KEGG and Reactome pathways, respectively. Based on PhenPathDB, PhenPathTOOL analyzes user-defined sets of phenotypes retrieving diseases, genes and functional terms which they share. This information can provide clues for interpreting the co-occurrence of phenotypes in a patient. Conclusions The resource allows finding molecular features useful to investigate diseases characterized by multiple phenotypes, and by this, it can help researchers and physicians in identifying molecular mechanisms and biological functions underlying the concomitant manifestation of phenotypes. The resource is freely available at http://phenpath.biocomp.unibo.it

    Huntingtin: A protein with a peculiar solvent accessible surface

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    Taking advantage of the last cryogenic electron microscopy structure of human hunt-ingtin, we explored with computational methods its physicochemical properties, focusing on the solvent accessible surface of the protein and highlighting a quite interesting mix of hydrophobic and hydrophilic patterns, with the prevalence of the latter ones. We then evaluated the probability of exposed residues to be in contact with other proteins, discovering that they tend to cluster in specific regions of the protein. We then found that the remaining portions of the protein surface can contain calcium-binding sites that we propose here as putative mediators for the protein to interact with membranes. Our findings are justified in relation to the present knowledge of huntingtin functional annotation

    Mapping OMIM Disease–Related Variations on Protein Domains Reveals an Association Among Variation Type, Pfam Models, and Disease Classes

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    Human genome resequencing projects provide an unprecedented amount of data about single-nucleotide variations occurring in protein-coding regions and often leading to observable changes in the covalent structure of gene products. For many of these variations, links to Online Mendelian Inheritance in Man (OMIM) genetic diseases are available and are reported in many databases that are collecting human variation data such as Humsavar. However, the current knowledge on the molecular mechanisms that are leading to diseases is, in many cases, still limited. For understanding the complex mechanisms behind disease insurgence, the identification of putative models, when considering the protein structure and chemico-physical features of the variations, can be useful in many contexts, including early diagnosis and prognosis. In this study, we investigate the occurrence and distribution of human disease–related variations in the context of Pfam domains. The aim of this study is the identification and characterization of Pfam domains that are statistically more likely to be associated with disease-related variations. The study takes into consideration 2,513 human protein sequences with 22,763 disease-related variations. We describe patterns of disease-related variation types in biunivocal relation with Pfam domains, which are likely to be possible markers for linking Pfam domains to OMIM diseases. Furthermore, we take advantage of the specific association between disease-related variation types and Pfam domains for clustering diseases according to the Human Disease Ontology, and we establish a relation among variation types, Pfam domains, and disease classes. We find that Pfam models are specific markers of patterns of variation types and that they can serve to bridge genes, diseases, and disease classes. Data are available as Supplementary Material for 1,670 Pfam models, including 22,763 disease-related variations associated to 3,257 OMIM diseases

    Highlighting human enzymes active in different metabolic pathways and diseases: The case study of EC 1.2.3.1 and EC 2.3.1.9

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    Enzymes are key proteins performing the basic functional activities in cells. In humans, enzymes can be also responsible for diseases, and the molecular mechanisms underlying the genotype to phenotype relationship are under investigation for diagnosis and medical care. Here, we focus on highlighting enzymes that are active in different metabolic pathways and become relevant hubs in protein interaction networks. We perform a statistics to derive our present knowledge on human metabolic pathways (the Kyoto Encyclopaedia of Genes and Genomes (KEGG)), and we found that activity aldehyde dehydrogenase (NAD(+)), described by Enzyme Commission number EC 1.2.1.3, and activity acetyl-CoA C-acetyltransferase (EC 2.3.1.9) are the ones most frequently involved. By associating functional activities (EC numbers) to enzyme proteins, we found the proteins most frequently involved in metabolic pathways. With our analysis, we found that these proteins are endowed with the highest numbers of interaction partners when compared to all the enzymes in the pathways and with the highest numbers of predicted interaction sites. As specific enzyme protein test cases, we focus on Alpha-Aminoadipic Semialdehyde Dehydrogenase (ALDH7A1, EC 2.3.1.9) and Acetyl-CoA acetyltransferase, cytosolic and mitochondrial (gene products of ACAT2 and ACAT1, respectively; EC 2.3.1.9). With computational approaches we show that it is possible, by starting from the enzyme structure, to highlight clues of their multiple roles in different pathways and of putative mechanisms promoting the association of genes to disease

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    A glance into mthfr deficiency at a molecular level

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    MTHFR deficiency still deserves an investigation to associate the phenotype to protein structure variations. To this aim, considering the MTHFR wild type protein structure, with a catalytic and a regulatory domain and taking advantage of state‐of‐the‐art computational tools, we explore the properties of 72 missense variations known to be disease associated. By computing the thermodynamic ΔΔG change according to a consensus method that we recently introduced, we find that 61% of the disease‐related variations destabilize the protein, are present both in the catalytic and regulatory domain and correspond to known biochemical deficiencies. The propensity of solvent accessible residues to be involved in protein‐protein interaction sites indicates that most of the interacting residues are located in the regulatory domain, and that only three of them, located at the interface of the functional protein homodimer, are both disease‐related and destabilizing. Finally, we compute the protein architecture with Hidden Markov Models, one from Pfam for the catalytic domain and the second computed in house for the regulatory domain. We show that patterns of disease‐associated, physicochemical variation types, both in the catalytic and regulatory domains, are unique for the MTHFR deficiency when mapped into the protein architecture

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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