NLStradamus: a simple Hidden Markov Model for nuclear localization signal prediction

<p>Abstract</p> <p>Background</p> <p>Nuclear localization signals (NLSs) are stretches of residues within a protein that are important for the regulated nuclear import of the protein. Of the many import pathways that exist in yeast, the best characterized is termed the 'classical' NLS pathway. The classical NLS contains specific patterns of basic residues and computational methods have been designed to predict the location of these motifs on proteins. The consensus sequences, or patterns, for the other import pathways are less well-understood.</p> <p>Results</p> <p>In this paper, we present an analysis of characterized NLSs in yeast, and find, despite the large number of nuclear import pathways, that NLSs seem to show similar patterns of amino acid residues. We test current prediction methods and observe a low true positive rate. We therefore suggest an approach using hidden Markov models (HMMs) to predict novel NLSs in proteins. We show that our method is able to consistently find 37% of the NLSs with a low false positive rate and that our method retains its true positive rate outside of the yeast data set used for the training parameters.</p> <p>Conclusion</p> <p>Our implementation of this model, NLStradamus, is made available at: <url>http://www.moseslab.csb.utoronto.ca/NLStradamus/</url></p

Graphene as Transparent Electrode for Direct Observation of Hole Photoemission from Silicon to Oxide

The outstanding electrical and optical properties of graphene make it an excellent alternative as a transparent electrode. Here we demonstrate the application of graphene as collector material in internal photoemission (IPE) spectroscopy; enabling the direct observation of both electron and hole injections at a Si/Al2O3 interface and successfully overcoming the long-standing difficulty of detecting holes injected from a semiconductor emitter in IPE measurements. The observed electron and hole barrier heights are 3.5 eV and 4.1 eV, respectively. Thus the bandgap of Al2O3 can be further deduced to be 6.5 eV, in close agreement with the valued obtained by vacuum ultraviolet spectroscopic ellipsometry analysis. The detailed optical modeling of a graphene/Al2O3/Si stack reveals that by using graphene in IPE measurements the carrier injection from the emitter is significantly enhanced and the contribution of carrier injection from the collector electrode is minimal. The method can be readily extended to various IPE test structures for a complete band alignment analysis and interface characterization.Comment: 15 pages, 5 figure

Nonlinear signalling networks and cell-to-cell variability transform external signals into broadly distributed or bimodal responses

We show theoretically and experimentally a mechanismbehind the emergence of wide or bimodal protein distributions in biochemical networks with nonlinear input-output characteristics (the dose-response curve) and variability in protein abundance. Large cell-to-cell variation in the nonlinear dose-response characteristics can be beneficial to facilitate two distinct groups of response levels as opposed to a graded response. Under the circumstances that we quantify mathematically, the two distinct responses can coexist within a cellular population, leading to the emergence of a bimodal protein distribution. Using flow cytometry, we demonstrate the appearance of wide distributions in the hypoxia-inducible factor-mediated response network in HCT116 cells. With help of our theoretical framework, we perform a novel calculation of the magnitude of cell-to-cell heterogeneity in the dose-response obtained experimentally

Minimum information and guidelines for reporting a Multiplexed Assay of Variant Effect

Multiplexed Assays of Variant Effect (MAVEs) have emerged as a powerful approach for interrogating thousands of genetic variants in a single experiment. The flexibility and widespread adoption of these techniques across diverse disciplines has led to a heterogeneous mix of data formats and descriptions, which complicates the downstream use of the resulting datasets. To address these issues and promote reproducibility and reuse of MAVE data, we define a set of minimum information standards for MAVE data and metadata and outline a controlled vocabulary aligned with established biomedical ontologies for describing these experimental designs

The structure of an NDR/LATS kinase – mob complex reveals a novel kinase-coactivator system and substrate docking mechanism.

Eukaryotic cells commonly use protein kinases in signaling systems that relay information and control a wide range of processes. These enzymes have a fundamentally similar structure, but achieve functional diversity through variable regions that determine how the catalytic core is activated and recruited to phosphorylation targets. "Hippo" pathways are ancient protein kinase signaling systems that control cell proliferation and morphogenesis; the NDR/LATS family protein kinases, which associate with "Mob" coactivator proteins, are central but incompletely understood components of these pathways. Here we describe the crystal structure of budding yeast Cbk1-Mob2, to our knowledge the first of an NDR/LATS kinase-Mob complex. It shows a novel coactivator-organized activation region that may be unique to NDR/LATS kinases, in which a key regulatory motif apparently shifts from an inactive binding mode to an active one upon phosphorylation. We also provide a structural basis for a substrate docking mechanism previously unknown in AGC family kinases, and show that docking interaction provides robustness to Cbk1's regulation of its two known in vivo substrates. Co-evolution of docking motifs and phosphorylation consensus sites strongly indicates that a protein is an in vivo regulatory target of this hippo pathway, and predicts a new group of high-confidence Cbk1 substrates that function at sites of cytokinesis and cell growth. Moreover, docking peptides arise in unstructured regions of proteins that are probably already kinase substrates, suggesting a broad sequential model for adaptive acquisition of kinase docking in rapidly evolving intrinsically disordered polypeptides

A quantitative literature-curated gold standard for kinase-substrate pairs

We describe the Yeast Kinase Interaction Database (KID, http://www.moseslab.csb.utoronto.ca/KID/), which contains high- and low-throughput data relevant to phosphorylation events. KID includes 6,225 low-throughput and 21,990 high-throughput interactions, from greater than 35,000 experiments. By quantitatively integrating these data, we identified 517 high-confidence kinase-substrate pairs that we consider a gold standard. We show that this gold standard can be used to assess published high-throughput datasets, suggesting that it will enable similar rigorous assessments in the future

Epidural Hematoma Following Cervical Spine Surgery.

STUDY DESIGN: A multicentered retrospective case series. OBJECTIVE: To determine the incidence and circumstances surrounding the development of a symptomatic postoperative epidural hematoma in the cervical spine. METHODS: Patients who underwent cervical spine surgery between January 1, 2005, and December 31, 2011, at 23 institutions were reviewed, and all patients who developed an epidural hematoma were identified. RESULTS: A total of 16 582 cervical spine surgeries were identified, and 15 patients developed a postoperative epidural hematoma, for a total incidence of 0.090%. Substantial variation between institutions was noted, with 11 sites reporting no epidural hematomas, and 1 site reporting an incidence of 0.76%. All patients initially presented with a neurologic deficit. Nine patients had complete resolution of the neurologic deficit after hematoma evacuation; however 2 of the 3 patients (66%) who had a delay in the diagnosis of the epidural hematoma had residual neurologic deficits compared to only 4 of the 12 patients (33%) who had no delay in the diagnosis or treatment (P = .53). Additionally, the patients who experienced a postoperative epidural hematoma did not experience any significant improvement in health-related quality-of-life metrics as a result of the index procedure at final follow-up evaluation. CONCLUSION: This is the largest series to date to analyze the incidence of an epidural hematoma following cervical spine surgery, and this study suggest that an epidural hematoma occurs in approximately 1 out of 1000 cervical spine surgeries. Prompt diagnosis and treatment may improve the chance of making a complete neurologic recovery, but patients who develop this complication do not show improvements in the health-related quality-of-life measurements

Population genomics of domestic and wild yeasts

The natural genetics of an organism is determined by the distribution of sequences of its genome. Here we present one- to four-fold, with some deeper, coverage of the genome sequences of over seventy isolates of the domesticated baker&#x27;s yeast, _Saccharomyces cerevisiae_, and its closest relative, the wild _S. paradoxus_, which has never been associated with human activity. These were collected from numerous geographic locations and sources (including wild, clinical, baking, wine, laboratory and food spoilage). These sequences provide an unprecedented view of the population structure, natural (and artificial) selection and genome evolution in these species. Variation in gene content, SNPs, indels, copy numbers and transposable elements provide insights into the evolution of different lineages. Phenotypic variation broadly correlates with global genome-wide phylogenetic relationships however there is no correlation with source. _S. paradoxus_ populations are well delineated along geographic boundaries while the variation among worldwide _S. cerevisiae_ isolates show less differentiation and is comparable to a single _S. paradoxus_ population. Rather than one or two domestication events leading to the extant baker&#x27;s yeasts, the population structure of _S. cerevisiae_ shows a few well defined geographically isolated lineages and many different mosaics of these lineages, supporting the notion that human influence provided the opportunity for outbreeding and production of new combinations of pre-existing variation

Multivariate Relations Aggregation Learning in Social Networks

Multivariate relations are general in various types of networks, such as biological networks, social networks, transportation networks, and academic networks. Due to the principle of ternary closures and the trend of group formation, the multivariate relationships in social networks are complex and rich. Therefore, in graph learning tasks of social networks, the identification and utilization of multivariate relationship information are more important. Existing graph learning methods are based on the neighborhood information diffusion mechanism, which often leads to partial omission or even lack of multivariate relationship information, and ultimately affects the accuracy and execution efficiency of the task. To address these challenges, this paper proposes the multivariate relationship aggregation learning (MORE) method, which can effectively capture the multivariate relationship information in the network environment. By aggregating node attribute features and structural features, MORE achieves higher accuracy and faster convergence speed. We conducted experiments on one citation network and five social networks. The experimental results show that the MORE model has higher accuracy than the GCN (Graph Convolutional Network) model in node classification tasks, and can significantly reduce time cost.Comment: 11 pages, 6 figure