Classification of time series by shapelet transformation

Time-series classification (TSC) problems present a specific challenge for classification algorithms: how to measure similarity between series. A \emph{shapelet} is a time-series subsequence that allows for TSC based on local, phase-independent similarity in shape. Shapelet-based classification uses the similarity between a shapelet and a series as a discriminatory feature. One benefit of the shapelet approach is that shapelets are comprehensible, and can offer insight into the problem domain. The original shapelet-based classifier embeds the shapelet-discovery algorithm in a decision tree, and uses information gain to assess the quality of candidates, finding a new shapelet at each node of the tree through an enumerative search. Subsequent research has focused mainly on techniques to speed up the search. We examine how best to use the shapelet primitive to construct classifiers. We propose a single-scan shapelet algorithm that finds the best $k$ shapelets, which are used to produce a transformed dataset, where each of the $k$ features represent the distance between a time series and a shapelet. The primary advantages over the embedded approach are that the transformed data can be used in conjunction with any classifier, and that there is no recursive search for shapelets. We demonstrate that the transformed data, in conjunction with more complex classifiers, gives greater accuracy than the embedded shapelet tree. We also evaluate three similarity measures that produce equivalent results to information gain in less time. Finally, we show that by conducting post-transform clustering of shapelets, we can enhance the interpretability of the transformed data. We conduct our experiments on 29 datasets: 17 from the UCR repository, and 12 we provide ourselve

Altered Serum IgG Levels to a-Synuclein in Dementia with Lewy Bodies and Alzheimer’s Disease.

Natural self-reactive antibodies in the peripheral blood may play a considerable role in the control of potentially toxic proteins that may otherwise accumulate in the aging brain. The significance of serum antibodies reactive against asynuclein is not well known. We explored serum IgG levels to monomeric a-synuclein in dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD) with a novel and validated highly sensitive ELISA assay. Antibody levels revealed stark differences in patients compared to healthy subjects and were dependent on diagnosis, disease duration and age. Anti-asynuclein IgG levels were increased in both patient groups, but in early DLB to a much greater extent than in AD. Increased antibody levels were most evident in younger patients, while with advanced age relatively low levels were observed, similar to healthy individuals, exhibiting stable antibody levels independent of age. Our data show the presence of differentially altered IgG levels against a-synuclein in DLB and AD, which may relate to a disturbed a-synuclein homeostasis triggered by the disease process. These observations may foster the development of novel, possibly preclinical biomarkers and immunotherapeutic strategies that target a-synuclein in neurodegenerative disease.Fil: Koehler, Niklas. Department of Psychiatry and Psychotherapy. EBERHARD-KARLS-UNIVERSITY;Fil: Stransky, Elke. Department of Psychiatry and Psychotherapy. EBERHARD-KARLS-UNIVERSITY;Fil: Shing, Mona. Department of Psychiatry and Psychotherapy. EBERHARD-KARLS-UNIVERSITY;Fil: Gaertner, Susanne. Department of Psychiatry and Psychotherapy, EBERHARD-KARLS-UNIVERSITY;Fil: Meyer, Mirjam. Department of Psychiatry and Psychotherapy. EBERHARD-KARLS-UNIVERSITY;Fil: Schreitmueller, Brigitte. Department of Psychiatry and Psychotherapy. EBERHARD-KARLS-UNIVERSITY;Fil: Leyhe, Thomas. Department of Psychiatry and Psychotherapy. EBERHARD-KARLS-UNIVERSITY;Fil: Laske, Cristoph. Department of Psychiatry and Psychotherapy. EBERHARD-KARLS-UNIVERSITY;Fil: Maetzler, Walter. Department of Neurodegeneration. HERTIE INSTITUTE FOR CLINICAL BRAIN RESEARCH;Fil: Kahle, Philipp. FUNCTIONAL NEUROGENETICS. HERTIE INSTITUTE FOR CLINICAL;Fil: Celej, Maria Soleda. MAX-PLANCK-INSTITUTE FOR BIOPHYSICAL CHEMISTRY; Consejo Nacional de Invest.cientif.y Tecnicas. Centro Cientifico Tecnol.conicet - Cordoba. Centro de Invest.en Qca.biol.de Cordoba (p);Fil: Jovin, Thomas M.. MAX-PLANCK-INSTITUTE FOR BIOPHYSICAL CHEMISTRY;Fil: Fallgatter, Andreas. Department of Psychiatry and Psychotherapy. EBERHARD-KARLS-UNIVERSITY;Fil: Batra, Anil. Department of Psychiatry and Psychotherapy. EBERHARD-KARLS-UNIVERSITY;Fil: Buchkremer, Gherard. Department of Psychiatry and Psychotherapy. EBERHARD-KARLS-UNIVERSITY;Fil: Schott, Klauss. Department of Psychiatry and Psychotherapy. EBERHARD-KARLS-UNIVERSITY;Fil: Richartz-Salzburger, Elke. Department of Psychiatry and Psychotherapy. EBERHARD-KARLS-UNIVERSITY

37^th plenary meeting report of the scientific, technical and economic committee for fisheries (PLEN-11-02)

The Scientific, Technical and Economic Committee for Fisheries hold its 37th plenary on 11-15 July 2011 in Copenhagen (Denmark). The terms of reference included both issues assessments of STECF Expert Working Group reports and additional requests submitted to the STECF by the Commission. Topics dealt with ranged from fisheries economics to management plan evaluation issues

Real-time state estimation of laboratory flows

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2007."June 2007."Includes bibliographical references (p. 51).In this project, we use a real time computer model to simulate a differentially heated laboratory annulus. The laboratory annulus allows us to study chaotic flows typical of the atmosphere. Our objective is to bring the numerical model into close alignment with the laboratory system. Parameter estimation and data assimilation of real time model runs with the tank experiment can be used to improve numerical model fidelity, provided the model operates in real time and the model parameters are in acceptable regimes. We describe how to modify the default configuration of the MITgcm to tackle this new problem. We also run laboratory experiments. Using an iterative process, we update the model parameters (such as diffusion and viscosity), and observe that in at least some regimes, there is excellent agreement between observations and simulations. Much of this effort required the development of infrastructure, which is discussed in this document. Finally, we create and test a complete, real-time system, with data sent across the network from a parallel computer running the numerical model to the laboratory computer, where data assimilation takes place. We further modify the model to allow it to pause mid-run, and restart with the most recent state estimates of velocity and temperature.by Scott Stransky.S.M

Scientific, Technical and Economic Committee for Fisheries. Evaluation of fishing effort regimes - Deep sea and Western waters (STECF-11-12)

EWG-11-11 meeting was held on 26 – 30 September 2011 in Cadiz (Spain). This Section of the report covers the Deep Sea and Western Waters and provides fleet specific trends in catch (including discards), nominal effort and catch (landings) per unit of effort in order to advise on fleet specific impacts on stocks under multiannual management plans. STECF reviewed the report during its November 2011 plenary meeting

Functional genomics reveals serine synthesis is essential in PHGDH-amplified breast cancer

Cancer cells adapt their metabolic processes to drive macromolecular biosynthesis for rapid cell growth and proliferation[superscript 1, 2]. RNA interference (RNAi)-based loss-of-function screening has proven powerful for the identification of new and interesting cancer targets, and recent studies have used this technology in vivo to identify novel tumour suppressor genes[superscript 3]. Here we developed a method for identifying novel cancer targets via negative-selection RNAi screening using a human breast cancer xenograft model at an orthotopic site in the mouse. Using this method, we screened a set of metabolic genes associated with aggressive breast cancer and stemness to identify those required for in vivo tumorigenesis. Among the genes identified, phosphoglycerate dehydrogenase (PHGDH) is in a genomic region of recurrent copy number gain in breast cancer and PHGDH protein levels are elevated in 70% of oestrogen receptor (ER)-negative breast cancers. PHGDH catalyses the first step in the serine biosynthesis pathway, and breast cancer cells with high PHGDH expression have increased serine synthesis flux. Suppression of PHGDH in cell lines with elevated PHGDH expression, but not in those without, causes a strong decrease in cell proliferation and a reduction in serine synthesis. We find that PHGDH suppression does not affect intracellular serine levels, but causes a drop in the levels of α-ketoglutarate, another output of the pathway and a tricarboxylic acid (TCA) cycle intermediate. In cells with high PHGDH expression, the serine synthesis pathway contributes approximately 50% of the total anaplerotic flux of glutamine into the TCA cycle. These results reveal that certain breast cancers are dependent upon increased serine pathway flux caused by PHGDH overexpression and demonstrate the utility of in vivo negative-selection RNAi screens for finding potential anticancer targets.Susan G. Komen Breast Cancer Foundation (Fellowship)Life Sciences Research Foundation (Fellowship)W. M. Keck FoundationDavid H. Koch Cancer Research FundAlexander and Margaret Stewart TrustNational Institutes of Health (U.S.) (Grant CA103866

Identification of mutations in the PYRIN-containing NLR genes (NLRP) in head and neck squamous cell carcinoma

Head and Neck Squamous Cell Carcinoma (HNSCC) encompasses malignancies that arise in the mucosa of the upper aerodigestive tract. Recent high throughput DNA sequencing revealed HNSCC genes mutations that contribute to several cancer cell characteristics, including dysregulation of cell proliferation and death, intracellular proinflammatory signaling, and autophagy. The PYRIN-domain containing NLR (Nucleotide-binding domain, Leucine rich Repeats - containing) proteins have recently emerged as pivotal modulators of cell death, autophagy, inflammation, and metabolism. Their close physiologic association with cancer development prompted us to determine whether mutations within the NLRP (PYRIN-containing NLR ) gene family were associated with HNSCC genome instability and their clinicopathologic correlations. Catastrophic mutational events underlie cancer cell genome instability and mark a point-of-no-return in cancer cell development and generation of heterogeneity. The mutation profiles of 62 patients with primary conventional type HNSCC excluding other histologic variants were analyzed. Associations were tested using Fisher's Exact test or Mann-Whitney U test. Mutations in NLRP were associated with elevated genome instability as characterized by higher mutation rates. Clinically, NLRP mutations were more frequently found in HNSCC arising in the floor of mouth (50.0%) in comparison with HNSCC at other head and neck locations (14.8%). These mutations were clustered at the leucine rich repeats region of NLRP proteins, and affected NLRP genes were mostly localized at chromosomes 11p15.4 and 19q13.42-19q13.43. Twenty novel NLRP mutations were identified in HNSCC, and mutations in this group of genes were correlated with increased cancer cell genome mutation rates, and such features could be a potential molecular biomarker of HNSCC genome instability. © 2014 Lei et al

Medulloblastoma Exome Sequencing Uncovers Subtype-Specific Somatic Mutations

Medulloblastomas are the most common malignant brain tumors in children1. Identifying and understanding the genetic events that drive these tumors is critical for the development of more effective diagnostic, prognostic and therapeutic strategies. Recently, our group and others described distinct molecular subtypes of medulloblastoma based on transcriptional and copy number profiles2–5. Here, we utilized whole exome hybrid capture and deep sequencing to identify somatic mutations across the coding regions of 92 primary medulloblastoma/normal pairs. Overall, medulloblastomas exhibit low mutation rates consistent with other pediatric tumors, with a median of 0.35 non-silent mutations per megabase. We identified twelve genes mutated at statistically significant frequencies, including previously known mutated genes in medulloblastoma such as CTNNB1, PTCH1, MLL2, SMARCA4 and TP53. Recurrent somatic mutations were identified in an RNA helicase gene, DDX3X, often concurrent with CTNNB1 mutations, and in the nuclear co-repressor (N-CoR) complex genes GPS2, BCOR, and LDB1, novel findings in medulloblastoma. We show that mutant DDX3X potentiates transactivation of a TCF promoter and enhances cell viability in combination with mutant but not wild type beta-catenin. Together, our study reveals the alteration of Wnt, Hedgehog, histone methyltransferase and now N-CoR pathways across medulloblastomas and within specific subtypes of this disease, and nominates the RNA helicase DDX3X as a component of pathogenic beta-catenin signaling in medulloblastoma

Mutational heterogeneity in cancer and the search for new cancer genes

Major international projects are now underway aimed at creating a comprehensive catalog of all genes responsible for the initiation and progression of cancer. These studies involve sequencing of matched tumor–normal samples followed by mathematical analysis to identify those genes in which mutations occur more frequently than expected by random chance. Here, we describe a fundamental problem with cancer genome studies: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds. The list includes many implausible genes (such as those encoding olfactory receptors and the muscle protein titin), suggesting extensive false positive findings that overshadow true driver events. Here, we show that this problem stems largely from mutational heterogeneity and provide a novel analytical methodology, MutSigCV, for resolving the problem. We apply MutSigCV to exome sequences from 3,083 tumor-normal pairs and discover extraordinary variation in (i) mutation frequency and spectrum within cancer types, which shed light on mutational processes and disease etiology, and (ii) mutation frequency across the genome, which is strongly correlated with DNA replication timing and also with transcriptional activity. By incorporating mutational heterogeneity into the analyses, MutSigCV is able to eliminate most of the apparent artefactual findings and allow true cancer genes to rise to attention