15 research outputs found

    MAPO: Mining and Recommending API Usage Patterns

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    To improve software productivity, when constructing new software systems, programmers often reuse existing libraries or frameworks by invoking methods provided in their APIs. Those API methods, however, are often complex and not well documented. To get familiar with how those API methods are used, programmers often exploit a source code search tool to search for code snippets that use the API methods of interest. However, the returned code snippets are often large in number, and the huge number of snippets places a barrier for programmers to locate useful ones. In order to help programmers overcome this barrier, we have developed an API usage mining framework and its supporting tool called MAPO (Mining API usage Pattern from Open source repositories) for mining API usage patterns automatically. A mined pattern describes that in a certain usage scenario, some API methods are frequently called together and their usages follow some sequential rules. MAPO further recommends the mined API usage patterns and their associated code snippets upon programmers' requests. Our experimental results show that with these patterns MAPO helps programmers locate useful code snippets more effectively than two state-of-the-art code search tools. To investigate whether MAPO can assist programmers in programming tasks, we further conducted an empirical study. The results show that using MAPO, programmers produce code with fewer bugs when facing relatively complex API usages, comparing with using the two state-of-the-art code search tools. ? 2009 Springer Berlin Heidelberg.EI

    Genome-wide identification of the genetic basis of amyotrophic lateral sclerosis

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    Amyotrophic lateral sclerosis (ALS) is a complex disease that leads to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies (GWASs) have discovered relatively few loci. We developed a machine learning approach called RefMap, which integrates functional genomics with GWAS summary statistics for gene discovery. With transcriptomic and epigenetic profiling of motor neurons derived from induced pluripotent stem cells (iPSCs), RefMap identified 690 ALS-associated genes that represent a 5-fold increase in recovered heritability. Extensive conservation, transcriptome, network, and rare variant analyses demonstrated the functional significance of candidate genes in healthy and diseased motor neurons and brain tissues. Genetic convergence between common and rare variation highlighted KANK1 as a new ALS gene. Reproducing KANK1 patient mutations in human neurons led to neurotoxicity and demonstrated that TDP-43 mislocalization, a hallmark pathology of ALS, is downstream of axonal dysfunction. RefMap can be readily applied to other complex diseases

    RETINOBLASTOMA RELATED1 Regulates Asymmetric Cell Divisions in Arabidopsis.

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    Formative, also called asymmetric, cell divisions produce daughter cells with different identities. Like other divisions, formative divisions rely first of all on the cell cycle machinery with centrally acting cyclin-dependent kinases (CDKs) and their cyclin partners to control progression through the cell cycle. However, it is still largely obscure how developmental cues are translated at the cellular level to promote asymmetric divisions. Here, we show that formative divisions in the shoot and root of the flowering plant Arabidopsis thaliana are controlled by a common mechanism that relies on the activity level of the Cdk1 homolog CDKA;1, with medium levels being sufficient for symmetric divisions but high levels being required for formative divisions. We reveal that the function of CDKA;1 in asymmetric cell divisions operates through a transcriptional regulation system that is mediated by the Arabidopsis Retinoblastoma homolog RBR1. RBR1 regulates not only cell cycle genes, but also, independent of the cell cycle transcription factor E2F, genes required for formative divisions and cell fate acquisition, thus directly linking cell proliferation with differentiation. This mechanism allows the implementation of spatial information, in the form of high kinase activity, with intracellular gating of developmental decisions

    Measurements of Entrainment and Mixing in Turbulent Jets

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    An experimental investigation of entrainment and mixing in the self-similar far field of an axisymmetric free turbulent jet in water is presented. Length and time scales for the flame length fluctuations of reacting jets are shown to be approximately equal to the local characteristic large scale length and time of the flow. It is also shown that instantaneous radial profiles of concentration across the jet do not resemble the mean concentration profile, indicating that the mean profile is a poor representation of the mixed fluid states within the jet. These instantaneous profiles also show that unmixed ambient fluid is transported throughout the entire extent of the jet, and that the mixed fluid composition within the jet can be fairly uniform in regions extending across a large part of the local jet diameter. Lastly, the amount of unmixed ambient fluid on the jet centerline is found to vary roughly periodically with a period approximately equal to the local characteristic large scale time of the flow. These results suggest that large scale transport mechanisms, displaying a characteristic organization, play an important role in entrainment and mixing in the far filed of turbulent jets

    Multiomic analysis reveals cell-type-specific molecular determinants of COVID-19 severity

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    The determinants of severe COVID-19 in healthy adults are poorly understood, which limits the opportunity for early intervention. We present a multiomic analysis using machine learning to characterize the genomic basis of COVID-19 severity. We use single-cell multiome profiling of human lungs to link genetic signals to cell-type-specific functions. We discover >1,000 risk genes across 19 cell types, which account for 77% of the SNP-based heritability for severe disease. Genetic risk is particularly focused within natural killer (NK) cells and T cells, placing the dysfunction of these cells upstream of severe disease. Mendelian randomization and single-cell profiling of human NK cells support the role of NK cells and further localize genetic risk to CD56bright NK cells, which are key cytokine producers during the innate immune response. Rare variant analysis confirms the enrichment of severe-disease-associated genetic variation within NK-cell risk genes. Our study provides insights into the pathogenesis of severe COVID-19 with potential therapeutic targets