Memetic Multilevel Hypergraph Partitioning

Hypergraph partitioning has a wide range of important applications such as VLSI design or scientific computing. With focus on solution quality, we develop the first multilevel memetic algorithm to tackle the problem. Key components of our contribution are new effective multilevel recombination and mutation operations that provide a large amount of diversity. We perform a wide range of experiments on a benchmark set containing instances from application areas such VLSI, SAT solving, social networks, and scientific computing. Compared to the state-of-the-art hypergraph partitioning tools hMetis, PaToH, and KaHyPar, our new algorithm computes the best result on almost all instances

Ty1 insertions in intergenic regions of the genome of Saccharomyces cerevisiae transcribed by RNA polymerase III have no detectable selective effect

The retrotransposon Ty1 of Saccharomyces cerevisiae inserts preferentially into intergenic regions in the vicinity of RNA polymerase III-transcribed genes. It has been suggested that this preference has evolved to minimize the deleterious effects of element transposition on the host genome, and thus to favor their evolutionary survival. This presupposes that such insertions have no selective effect. However, there has been no direct test of this hypothesis. Here we construct a series of strains containing single Ty1 insertions in the vicinity of tRNA genes, or in the rDNA cluster on chromosome XII, which are otherwise isogenic to strain 337, containing zero Ty1 elements. Competition experiments between 337 and the strains containing single Ty1 insertions revealed that in all cases, the Ty1 insertions have no selective effect in rich medium. These results are thus consistent with the hypothesis that the insertion site preference of Ty1 elements has evolved to minimize the deleterious effects of transposition on the host genome.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72266/1/S1567-1356_03_00199-5.pd

Accelerated seawater ageing and fatigue performance of glass fibre reinforced thermoplastic composites for marine and tidal energy applications

The use of thermoplastic composites as a sustainable alternative to thermosets is gaining increasing popularity due to their improved recyclability at the end of life. The fatigue performance of glass fibre/acrylic, glass fibre/acrylic- polyphenylene ether, and glass fibre/epoxy specimens, under three distinct upper stress levels (R-ratio=0.1; f=5 Hz) was studied. S-N curves were established for these specimens both before and after immersing them for three months in seawater (temperature: 50°C). The dry thermoplastic composites exhibited similar fatigue performance to the thermoset counterpart at higher stress levels, with thermosets showing greater endurance at lower stress levels. Interestingly, the aged specimens showed comparable fatigue endurance, with a slight advantage in favour of the thermoplastic composites and less variability in their data. This study offers important insights into the fatigue performance of thermoplastic composites, emphasising their potential as sustainable alternatives to conventional thermoset composites for various marine applications

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics

The Cancer Genome Atlas (TCGA) has catalyzed systematic characterization of diverse genomic alterations underlying human cancers. At this historic junction marking the completion of genomic characterization of over 11,000 tumors from 33 cancer types, we present our current understanding of the molecular processes governing oncogenesis. We illustrate our insights into cancer through synthesis of the findings of the TCGA PanCancer Atlas project on three facets of oncogenesis: (1) somatic driver mutations, germline pathogenic variants, and their interactions in the tumor; (2) the influence of the tumor genome and epigenome on transcriptome and proteome; and (3) the relationship between tumor and the microenvironment, including implications for drugs targeting driver events and immunotherapies. These results will anchor future characterization of rare and common tumor types, primary and relapsed tumors, and cancers across ancestry groups and will guide the deployment of clinical genomic sequencing

Somatic Mutational Landscape of Splicing Factor Genes and Their Functional Consequences across 33 Cancer Types

Hotspot mutations in splicing factor genes have been recently reported at high frequency in hematological malignancies, suggesting the importance of RNA splicing in cancer. We analyzed whole-exome sequencing data across 33 tumor types in The Cancer Genome Atlas (TCGA), and we identified 119 splicing factor genes with significant non-silent mutation patterns, including mutation over-representation, recurrent loss of function (tumor suppressor-like), or hotspot mutation profile (oncogene-like). Furthermore, RNA sequencing analysis revealed altered splicing events associated with selected splicing factor mutations. In addition, we were able to identify common gene pathway profiles associated with the presence of these mutations. Our analysis suggests that somatic alteration of genes involved in the RNA-splicing process is common in cancer and may represent an underappreciated hallmark of tumorigenesis