The Human Diabetes Proteome Project (HDPP): The 2014 update

Schvartz, Domitille; Bergsten, Patrik; Baek, Kwang‐Hyun; Rosa, Ana-Paulina Barba de la; Cantley, James; Dayon, Loı̈c; Finamore, Francesco; Fontana, Pierre; Gaudet, Pascale; Goo, Young Ah; Moulder, Robert; Johnson, Janice; Konvalinka, Ana; Mulder, Hindrik; Priego‐Capote, Feliciano; Sechi, Salvatore; Snyder, Kathleen; Tiss, Ali; Wiederkehr, Andreas; Xenarios, Ioannis; Kussmann, Martin; Sanchez, Jean‐Charles

doi:10.1016/j.trprot.2015.03.001

Cited by 7 publications

(2 citation statements)

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“…As we computed T2D relevance scores for proteins from the last five years' of literature, we expected well-known T2D proteins to get the highest scores. We benchmarked this by examining how well the scoring scheme for this project was able to find three sets of T2D proteins via ROC curves; 1) T2D proteins from the Human Diabetes Proteome Project [33], 2) a manual benchmark list of proteins selected for this project, and 3) proteins from public T2D pathways (KEGG [34][35][36], WikiPathways [37]) or annotated in UniProt [38] as relevant for T2D (Fig 4, left and centre). All had AUCs above 0.88, i.e.…”

Section: T2d Relevance Of Proteinsmentioning

confidence: 99%

Semantic text mining in early drug discovery for type 2 diabetes

et al. 2020

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BackgroundSurveying the scientific literature is an important part of early drug discovery; and with the ever-increasing amount of biomedical publications it is imperative to focus on the most interesting articles. Here we present a project that highlights new understanding (e.g. recently discovered modes of action) and identifies potential drug targets, via a novel, data-driven text mining approach to score type 2 diabetes (T2D) relevance. We focused on monitoring trends and jumps in T2D relevance to help us be timely informed of important breakthroughs. MethodsWe extracted over 7 million n-grams from PubMed abstracts and then clustered around 240,000 linked to T2D into almost 50,000 T2D relevant 'semantic concepts'. To score papers, we weighted the concepts based on co-mentioning with core T2D proteins. A protein's T2D relevance was determined by combining the scores of the papers mentioning it in the five preceding years. Each week all proteins were ranked according to their T2D relevance. Furthermore, the historical distribution of changes in rank from one week to the next was used to calculate the significance of a change in rank by T2D relevance for each protein. ResultsWe show that T2D relevant papers, even those not mentioning T2D explicitly, were prioritised by relevant semantic concepts. Well known T2D proteins were therefore enriched among the top scoring proteins. Our 'high jumpers' identified important past developments

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Section: T2d Relevance Of Proteinsmentioning

confidence: 99%

Semantic text mining in early drug discovery for type 2 diabetes

et al. 2020

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“…The HDPP will disseminate approved measurement methodologies for the 24 targets, which could be a common project for HDPP partners. The group decided on objectives for 2015–2016 and published them in Translational Proteomics …”

Section: B/d-hpp Workhops At 2015 Hupo World Congress In Vancouvermentioning

confidence: 99%

Highlights of the Biology and Disease-driven Human Proteome Project, 2015–2016

et al. 2016

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The Biology and Disease-driven Human Proteome Project (B/D-HPP) is aimed at supporting and enhancing the broad use of state-of-the-art proteomic methods to characterize and quantify proteins for in-depth understanding of the molecular mechanisms of biological processes and human disease. Based on a foundation of the pre-existing HUPO initiatives begun in 2002, the B/D-HPP is designed to provide standardized methods and resources for mass spectrometry and specific protein affinity reagents and facilitate accessibility of these resources to the broader life sciences research and clinical communities. Currently there are 22 B/D-HPP initiatives and 3 closely related HPP resource pillars. The B/D-HPP groups are working to define sets of protein targets that are highly relevant to each particular field to deliver relevant assays for the measurement of these selected targets and to disseminate and make publicly accessible the information and tools generated. Major developments are the 2016 publications of the Human SRM Atlas and of “popular protein sets” for six organ systems. Here we present the current activities and plans of the BD-HPP initiatives as highlighted in numerous B/D-HPP workshops at the 14th annual HUPO 2015 World Congress of Proteomics in Vancouver, Canada.

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