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  • Data from "The predictive performance of short-linear motif features in the prediction of calmodulin-binding proteins"
    WSU Dataset

    Authors
    Yixun Li
    Mina Maleki
    Nicholas Carruthers
    Paul M. Stemmer
    2 more author(s)...
    Description

    The prediction of calmodulin-binding (CaM-binding) proteins plays a very important role in the fields of biology and biochemistry, because the calmodulin protein binds and regulates a multitude of protein targets affecting different cellular processes. Computational methods that can accurately identify CaM-binding proteins and CaM-binding domains would accelerate research in calcium signaling and calmodulin function. Short-linear motifs (SLiMs), on the other hand, have been effectively used as features for analyzing protein-protein interactions, though their properties have not been utilized in the prediction of CaM-binding proteins. In this study, researchers propose a new method for the prediction of CaM-binding proteins based on both the total and average scores of known and new SLiMs in protein sequences using a new scoring method called sliding window scoring (SWS) as features for the prediction module. A dataset of 194 manually curated human CaM-binding proteins and 193 mitochondrial proteins have been obtained and used for testing the proposed model.

    Subject
    Biology
    Access Rights
    Free to all
  • Glass promotes the differentiation of both neuronal and non-neuronal cells in the Drosophila eye
    WSU Dataset

    Authors
    Carolyn A. Morrison
    Hao Chen
    Tiffany Cook
    Stuart Brown
    1 more author(s)...
    Description

    Multiple cell types can be specified from a single pool of progenitors through the combinatorial activity of transcriptional regulators, which activate distinct developmental programs to establish different cell fates. The zinc finger transcription factor Glass is required for neuronal progenitors in the Drosophila eye imaginal disc to acquire a photoreceptor identity. Glass is also expressed in non-neuronal cone and pigment cells, but its role in these cells is unknown. To examine how Glass activity is affected by the cellular context, the researchers misexpressed it in different tissues. When expressed in neuroblasts of the larval brain or in epithelial cells of the wing disc, Glass activated both a common core set of target genes and distinct gene sets specific to each tissue. In addition to photoreceptor-specific genes, Glass induced markers of cone and pigment cells. Cell type-specific glass mutations generated in cone or pigment cells using somatic CRISPR revealed autonomous developmental defects, and expressing Glass specifically in these cells partially rescued glass mutant phenotypes. Glass thus acts in both neuronal and non-neuronal cells to promote their differentiation into functional components of the eye, suggesting that it is a determinant of organ identity.

    Subject
    Biology
    Access Rights
    Free to all
  • Data from "The prediction of late-onset preeclampsia: Results from a longitudinal proteomics study"
    WSU Dataset

    Authors
    Offer Erez
    Roberto Romero
    Eli Maymon
    Piya Chaemsaithong
    6 more author(s)...
    Description

    Preeclampsia, a frequent complication of pregnancy that affects 5%-8% of all gestations, is a leading cause of maternal, and perinatal morbidity and mortality. Over the last decade, it has become clear that preeclampsia is not a single disorder but a syndrome with many etiologies, such as abnormal placentation, utero-placental ischemia, vascular disorders of the placenta, insulin resistance, systemic maternal inflammation, endothelial dysfunction, and imbalance of angiogenic and anti-angiogenic proteins. A case-control longitudinal study was conducted, including 90 patients with normal pregnancies and 76 patients with late-onset preeclampsia (diagnosed at ≥34 weeks of gestation). Maternal plasma samples were collected throughout gestation (normal pregnancy: 2–6 samples per patient, median of 2; late-onset preeclampsia: 2–6, median of 5). The abundance of 1,125 proteins was measured using an aptamers-based proteomics technique. Protein abundance in normal pregnancies was modeled using linear mixed-effects models to estimate mean abundance as a function of gestational age. Data was then expressed as multiples of-the-mean (MoM) values in normal pregnancies. Multi-marker prediction models were built using data from one of five gestational age intervals.

    Subject
    Medicine & Health
    Timeframe
    2007 - 2013
    Access Rights
    Free to all

 

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