824 research outputs found

    Economic tools to promote transparency and comparability in the Paris Agreement

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    The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years1. An important policy task will be to assess and compare these contributions2, 3. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects

    BSSF: a fingerprint based ultrafast binding site similarity search and function analysis server

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    <p>Abstract</p> <p>Background</p> <p>Genome sequencing and post-genomics projects such as structural genomics are extending the frontier of the study of sequence-structure-function relationship of genes and their products. Although many sequence/structure-based methods have been devised with the aim of deciphering this delicate relationship, there still remain large gaps in this fundamental problem, which continuously drives researchers to develop novel methods to extract relevant information from sequences and structures and to infer the functions of newly identified genes by genomics technology.</p> <p>Results</p> <p>Here we present an ultrafast method, named BSSF(Binding Site Similarity & Function), which enables researchers to conduct similarity searches in a comprehensive three-dimensional binding site database extracted from PDB structures. This method utilizes a fingerprint representation of the binding site and a validated statistical Z-score function scheme to judge the similarity between the query and database items, even if their similarities are only constrained in a sub-pocket. This fingerprint based similarity measurement was also validated on a known binding site dataset by comparing with geometric hashing, which is a standard 3D similarity method. The comparison clearly demonstrated the utility of this ultrafast method. After conducting the database searching, the hit list is further analyzed to provide basic statistical information about the occurrences of Gene Ontology terms and Enzyme Commission numbers, which may benefit researchers by helping them to design further experiments to study the query proteins.</p> <p>Conclusions</p> <p>This ultrafast web-based system will not only help researchers interested in drug design and structural genomics to identify similar binding sites, but also assist them by providing further analysis of hit list from database searching.</p

    BSSF: a fingerprint based ultrafast binding site similarity search and function analysis server

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Genome sequencing and post-genomics projects such as structural genomics are extending the frontier of the study of sequence-structure-function relationship of genes and their products. Although many sequence/structure-based methods have been devised with the aim of deciphering this delicate relationship, there still remain large gaps in this fundamental problem, which continuously drives researchers to develop novel methods to extract relevant information from sequences and structures and to infer the functions of newly identified genes by genomics technology.</p> <p>Results</p> <p>Here we present an ultrafast method, named BSSF(Binding Site Similarity & Function), which enables researchers to conduct similarity searches in a comprehensive three-dimensional binding site database extracted from PDB structures. This method utilizes a fingerprint representation of the binding site and a validated statistical Z-score function scheme to judge the similarity between the query and database items, even if their similarities are only constrained in a sub-pocket. This fingerprint based similarity measurement was also validated on a known binding site dataset by comparing with geometric hashing, which is a standard 3D similarity method. The comparison clearly demonstrated the utility of this ultrafast method. After conducting the database searching, the hit list is further analyzed to provide basic statistical information about the occurrences of Gene Ontology terms and Enzyme Commission numbers, which may benefit researchers by helping them to design further experiments to study the query proteins.</p> <p>Conclusions</p> <p>This ultrafast web-based system will not only help researchers interested in drug design and structural genomics to identify similar binding sites, but also assist them by providing further analysis of hit list from database searching.</p

    Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

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    Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

    The Ascent of the Abundant: How Mutational Networks Constrain Evolution

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    Evolution by natural selection is fundamentally shaped by the fitness landscapes in which it occurs. Yet fitness landscapes are vast and complex, and thus we know relatively little about the long-range constraints they impose on evolutionary dynamics. Here, we exhaustively survey the structural landscapes of RNA molecules of lengths 12 to 18 nucleotides, and develop a network model to describe the relationship between sequence and structure. We find that phenotype abundance—the number of genotypes producing a particular phenotype—varies in a predictable manner and critically influences evolutionary dynamics. A study of naturally occurring functional RNA molecules using a new structural statistic suggests that these molecules are biased toward abundant phenotypes. This supports an “ascent of the abundant” hypothesis, in which evolution yields abundant phenotypes even when they are not the most fit

    Whole Genome Expression Array Profiling Highlights Differences in Mucosal Defense Genes in Barrett's Esophagus and Esophageal Adenocarcinoma

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    Esophageal adenocarcinoma (EAC) has become a major concern in Western countries due to rapid rises in incidence coupled with very poor survival rates. One of the key risk factors for the development of this cancer is the presence of Barrett's esophagus (BE), which is believed to form in response to repeated gastro-esophageal reflux. In this study we performed comparative, genome-wide expression profiling (using Illumina whole-genome Beadarrays) on total RNA extracted from esophageal biopsy tissues from individuals with EAC, BE (in the absence of EAC) and those with normal squamous epithelium. We combined these data with publically accessible raw data from three similar studies to investigate key gene and ontology differences between these three tissue states. The results support the deduction that BE is a tissue with enhanced glycoprotein synthesis machinery (DPP4, ATP2A3, AGR2) designed to provide strong mucosal defenses aimed at resisting gastro-esophageal reflux. EAC exhibits the enhanced extracellular matrix remodeling (collagens, IGFBP7, PLAU) effects expected in an aggressive form of cancer, as well as evidence of reduced expression of genes associated with mucosal (MUC6, CA2, TFF1) and xenobiotic (AKR1C2, AKR1B10) defenses. When our results are compared to previous whole-genome expression profiling studies keratin, mucin, annexin and trefoil factor gene groups are the most frequently represented differentially expressed gene families. Eleven genes identified here are also represented in at least 3 other profiling studies. We used these genes to discriminate between squamous epithelium, BE and EAC within the two largest cohorts using a support vector machine leave one out cross validation (LOOCV) analysis. While this method was satisfactory for discriminating squamous epithelium and BE, it demonstrates the need for more detailed investigations into profiling changes between BE and EAC

    Literature Mining for the Discovery of Hidden Connections between Drugs, Genes and Diseases

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    The scientific literature represents a rich source for retrieval of knowledge on associations between biomedical concepts such as genes, diseases and cellular processes. A commonly used method to establish relationships between biomedical concepts from literature is co-occurrence. Apart from its use in knowledge retrieval, the co-occurrence method is also well-suited to discover new, hidden relationships between biomedical concepts following a simple ABC-principle, in which A and C have no direct relationship, but are connected via shared B-intermediates. In this paper we describe CoPub Discovery, a tool that mines the literature for new relationships between biomedical concepts. Statistical analysis using ROC curves showed that CoPub Discovery performed well over a wide range of settings and keyword thesauri. We subsequently used CoPub Discovery to search for new relationships between genes, drugs, pathways and diseases. Several of the newly found relationships were validated using independent literature sources. In addition, new predicted relationships between compounds and cell proliferation were validated and confirmed experimentally in an in vitro cell proliferation assay. The results show that CoPub Discovery is able to identify novel associations between genes, drugs, pathways and diseases that have a high probability of being biologically valid. This makes CoPub Discovery a useful tool to unravel the mechanisms behind disease, to find novel drug targets, or to find novel applications for existing drugs
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