Publications by authors named "Maria Famiglietti"

Large-scale next-generation sequencing (NGS) germline testing is technically feasible today, but variant interpretation represents a major bottleneck in analysis workflows. This includes extensive variant prioritization, annotation, and time-consuming evidence curation. The scale of the interpretation problem is massive, and variants of uncertain significance (VUSs) are a challenge to personalized medicine.

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Article Synopsis
  • High-quality bioinformatics resources are essential for analyzing patient-derived clinical samples, translating complex biological data from journal articles into structured formats for better accessibility and productivity in research.
  • The objective of this study was to update key public-domain resources to enhance support for Alzheimer's disease research by collaborating with the clinical research community to identify important proteins.
  • As a result, significant data updates were made across several databases, enhancing the understanding of Alzheimer's disease through improved protein entries, molecular interaction networks, and the availability of organized resources for researchers.
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Article Synopsis
  • Manually curating biomedical knowledge is important for creating a precise information service, but traditional methods of document triage using queries in PubMed often yield poor results.
  • To improve this process, a machine-learning assisted triage method was developed, training deep learning models on curated publications from databases like UniProtKB/Swiss-Prot and the NHGRI-EBI GWAS Catalog.
  • This new method significantly increases classification accuracy, achieving precision that is up to 3 times higher than traditional methods while finding additional relevant publications, allowing human curators to focus on more complex tasks.
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Motivation: Biological knowledgebases, such as UniProtKB/Swiss-Prot, constitute an essential component of daily scientific research by offering distilled, summarized and computable knowledge extracted from the literature by expert curators. While knowledgebases play an increasingly important role in the scientific community, their ability to keep up with the growth of biomedical literature is under scrutiny. Using UniProtKB/Swiss-Prot as a case study, we address this concern via multiple literature triage approaches.

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Advances in high-throughput and advanced technologies allow researchers to routinely perform whole genome and proteome analysis. For this purpose, they need high-quality resources providing comprehensive gene and protein sets for their organisms of interest. Using the example of the human proteome, we will describe the content of a complete proteome in the UniProt Knowledgebase (UniProtKB).

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During the last few years, next-generation sequencing (NGS) technologies have accelerated the detection of genetic variants resulting in the rapid discovery of new disease-associated genes. However, the wealth of variation data made available by NGS alone is not sufficient to understand the mechanisms underlying disease pathogenesis and manifestation. Multidisciplinary approaches combining sequence and clinical data with prior biological knowledge are needed to unravel the role of genetic variants in human health and disease.

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UniProtKB/Swiss-Prot (http://beta.uniprot.org/uniprot; last accessed: 19 October 2007) is a manually curated knowledgebase providing information on protein sequences and functional annotation.

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