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  • Articles  (113)
  • Computer Science  (113)
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  • Articles  (113)
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  • 1
    Electronic Resource
    Electronic Resource
    Correlation of echoencephalographic findings and neurodevelopmental outcome: Intracranial hemorrhage and ventriculomegaly in infants of birth weight 1,000 grams or less (1987)
    Springer
    Journal of clinical monitoring and computing 3 (1987), S. 178-186 
    Details
    ISSN: 1573-2614
    Keywords: Measurement techniques: echoencephalography ; Hemorrhage ; cerebral ; Brain: hemorrhage ; hydrocephalus ; Complications: neurologic ; Child development disorders ; Infant ; premature: diseases
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Medicine
    Notes: Abstract Echoencephalograms were obtained for 118 of 121 successive infants who were admitted to the Stanford intensive care nursery, weighed 1,000 g or less at birth, and survived long enough for at least one study to be performed. Eightyeight of these infants survived and were followed up for 1 to 3 years; psychometric testing (Bayley Scales of Infant Development, Stanford-Binet Intelligence Scale, or both) was performed on 81% of these infants. Subependymal-intraventricular hemorrhages or intraparenchymal hemorrhages were associated with impaired development, but ventriculomegaly was not. The absence of echoencephalographic abnormalities did not exclude the possibility of impaired development in many infants. Periventricular leukomalacia was not observed. These data support independent scoring of subependymal intraventricular hemorrhages, intraparenchymal hemorrhages, and ventriculomegaly, rather than use of combined scales for prognostic purposes.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01695940
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  • 2
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    Gene Expression Signatures Based on Variability can Robustly Predict Tumor Progression and Prognosis (2015)
    Libertas Academica
    Details
    Publication Date: 2015-06-08
    Description: Gene expression signatures are commonly used to create cancer prognosis and diagnosis methods, yet only a small number of them are successfully deployed in the clinic since many fail to replicate performance on subsequent validation. A primary reason for this lack of reproducibility is the fact that these signatures attempt to model the highly variable and unstable genomic behavior of cancer. Our group recently introduced gene expression anti-profiles as a robust methodology to derive gene expression signatures based on the observation that while gene expression measurements are highly heterogeneous across tumors of a specific cancer type relative to the normal tissue, their degree of deviation from normal tissue expression in specific genes involved in tissue differentiation is a stable tumor mark that is reproducible across experiments and cancer types. Here we show that constructing gene expression signatures based on variability and the anti-profile approach yields classifiers capable of successfully distinguishing benign growths from cancerous growths based on deviation from normal expression. We then show that this same approach generates stable and reproducible signatures that predict probability of relapse and survival based on tumor gene expression. These results suggest that using the anti-profile framework for the discovery of genomic signatures is an avenue leading to the development of reproducible signatures suitable for adoption in clinical settings.
    Electronic ISSN: 1176-9351
    Topics: Computer Science , Medicine
    Published by Libertas Academica
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  • 3
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    PsyGeNET: a knowledge platform on psychiatric disorders and their genes (2015)
    Oxford University Press
    Details
    Publication Date: 2015-09-11
    Description: : PsyGeNET (Psychiatric disorders and Genes association NETwork) is a knowledge platform for the exploratory analysis of psychiatric diseases and their associated genes. PsyGeNET is composed of a database and a web interface supporting data search, visualization, filtering and sharing. PsyGeNET integrates information from DisGeNET and data extracted from the literature by text mining, which has been curated by domain experts. It currently contains 2642 associations between 1271 genes and 37 psychiatric disease concepts. In its first release, PsyGeNET is focused on three psychiatric disorders: major depression, alcohol and cocaine use disorders. PsyGeNET represents a comprehensive, open access resource for the analysis of the molecular mechanisms underpinning psychiatric disorders and their comorbidities. Availability and implementation: The PysGeNET platform is freely available at http://www.psygenet.org/ . The PsyGeNET database is made available under the Open Database License ( http://opendatacommons.org/licenses/odbl/1.0/ ). Contact: lfurlong@imim.es Supplementary information : Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 4
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    Humboldts enigma: What causes global patterns of mountain biodiversity? (2019)
    American Association for the Advancement of Science (AAAS)
    In: Science
    Details
    Publication Date: 2019
    Description: 〈p〉Mountains contribute disproportionately to the terrestrial biodiversity of Earth, especially in the tropics, where they host hotspots of extraordinary and puzzling richness. With about 25% of all land area, mountain regions are home to more than 85% of the world’s species of amphibians, birds, and mammals, many entirely restricted to mountains. Biodiversity varies markedly among these regions. Together with the extreme species richness of some tropical mountains, this variation has proven challenging to explain under traditional climatic hypotheses. However, the complex climatic characteristics of rugged mountain regions differ fundamentally from those of lowland regions, likely playing a key role in generating and maintaining diversity. With ongoing global changes in climate and land use, the role of mountains as refugia for biodiversity may well come under threat.〈/p〉
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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  • 5
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    Privacy-preserving microbiome analysis using secure computation (2016)
    Oxford University Press
    Details
    Publication Date: 2016-06-16
    Description: Motivation: Developing targeted therapeutics and identifying biomarkers relies on large amounts of research participant data. Beyond human DNA, scientists now investigate the DNA of micro-organisms inhabiting the human body. Recent work shows that an individual’s collection of microbial DNA consistently identifies that person and could be used to link a real-world identity to a sensitive attribute in a research dataset. Unfortunately, the current suite of DNA-specific privacy-preserving analysis tools does not meet the requirements for microbiome sequencing studies. Results: To address privacy concerns around microbiome sequencing, we implement metagenomic analyses using secure computation. Our implementation allows comparative analysis over combined data without revealing the feature counts for any individual sample. We focus on three analyses and perform an evaluation on datasets currently used by the microbiome research community. We use our implementation to simulate sharing data between four policy-domains. Additionally, we describe an application of our implementation for patients to combine data that allows drug developers to query against and compensate patients for the analysis. Availability and implementation: The software is freely available for download at: http://cbcb.umd.edu/~hcorrada/projects/secureseq.html Supplementary information: Supplementary data are available at Bioinformatics online. Contact: hcorrada@umiacs.umd.edu
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 6
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    methylFlow: cell-specific methylation pattern reconstruction from high-throughput bisulfite-converted DNA sequencing (2016)
    Oxford University Press
    Details
    Publication Date: 2016-06-01
    Description: Motivation: DNA methylation aberrations are now known to, almost universally, accompany the initiation and progression of cancers. In particular, the colon cancer epigenome contains specific genomic regions that, along with differences in methylation levels with respect to normal colon tissue, also show increased epigenetic and gene expression heterogeneity at the population level, i.e. across tumor samples, in comparison with other regions in the genome. Tumors are highly heterogeneous at the clonal level as well, and the relationship between clonal and population heterogeneity is poorly understood. Results: We present an approach that uses sequencing reads from high-throughput sequencing of bisulfite-converted DNA to reconstruct heterogeneous cell populations by assembling cell-specific methylation patterns. Our methodology is based on the solution of a specific class of minimum cost network flow problems. We use our methods to analyze the relationship between clonal heterogeneity and population heterogeneity in high-coverage data from multiple samples of colon tumor and matched normal tissues. Availability and implementation : http://github.com/hcorrada/methylFlow . Contact: hcorrada@umiacs.umd.edu Supplementary information: Supplementary information is available at Bioinformatics online .
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 7
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    DisGeNET-RDF: harnessing the innovative power of the Semantic Web to explore the genetic basis of diseases (2016)
    Oxford University Press
    Details
    Publication Date: 2016-07-09
    Description: Motivation: DisGeNET-RDF makes available knowledge on the genetic basis of human diseases in the Semantic Web. Gene-disease associations (GDAs) and their provenance metadata are published as human-readable and machine-processable web resources. The information on GDAs included in DisGeNET-RDF is interlinked to other biomedical databases to support the development of bioinformatics approaches for translational research through evidence-based exploitation of a rich and fully interconnected linked open data. Availability and implementation: http://rdf.disgenet.org/ Contact: support@disgenet.org
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 8
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    Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research (2015)
    BioMed Central
    Details
    Publication Date: 2015-02-23
    Description: Background: Current biomedical research needs to leverage and exploit the large amount of information reported in scientific publications. Automated text mining approaches, in particular those aimed at finding relationships between entities, are key for identification of actionable knowledge from free text repositories. We present the BeFree system aimed at identifying relationships between biomedical entities with a special focus on genes and their associated diseases. Results: By exploiting morpho-syntactic information of the text, BeFree is able to identify gene-disease, drug-disease and drug-target associations with state-of-the-art performance. The application of BeFree to real-case scenarios shows its effectiveness in extracting information relevant for translational research. We show the value of the gene-disease associations extracted by BeFree through a number of analyses and integration with other data sources. BeFree succeeds in identifying genes associated to a major cause of morbidity worldwide, depression, which are not present in other public resources. Moreover, large-scale extraction and analysis of gene-disease associations, and integration with current biomedical knowledge, provided interesting insights on the kind of information that can be found in the literature, and raised challenges regarding data prioritization and curation. We found that only a small proportion of the gene-disease associations discovered by using BeFree is collected in expert-curated databases. Thus, there is a pressing need to find alternative strategies to manual curation, in order to review, prioritize and curate text-mining data and incorporate it into domain-specific databases. We present our strategy for data prioritization and discuss its implications for supporting biomedical research and applications. Conclusions: BeFree is a novel text mining system that performs competitively for the identification of gene-disease, drug-disease and drug-target associations. Our analyses show that mining only a small fraction of MEDLINE results in a large dataset of gene-disease associations, and only a small proportion of this dataset is actually recorded in curated resources (2%), raising several issues on data prioritization and curation. We propose that joint analysis of text mined data with data curated by experts appears as a suitable approach to both assess data quality and highlight novel and interesting information.
    Electronic ISSN: 1471-2105
    Topics: Biology , Computer Science
    Published by BioMed Central
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  • 9
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    BlindCall: ultra-fast base-calling of high-throughput sequencing data by blind deconvolution (2014)
    Oxford University Press
    Details
    Publication Date: 2014-04-25
    Description: Motivation: Base-calling of sequencing data produced by high-throughput sequencing platforms is a fundamental process in current bioinformatics analysis. However, existing third-party probabilistic or machine-learning methods that significantly improve the accuracy of base-calls on these platforms are impractical for production use due to their computational inefficiency. Results: We directly formulate base-calling as a blind deconvolution problem and implemented BlindCall as an efficient solver to this inverse problem. BlindCall produced base-calls at accuracy comparable to state-of-the-art probabilistic methods while processing data at rates 10 times faster in most cases. The computational complexity of BlindCall scales linearly with read length making it better suited for new long-read sequencing technologies. Availability and Implementation: BlindCall is implemented as a set of Matlab scripts available for download at http://cbcb.umd.edu/~hcorrada/secgen . Contact: hcorrada@umiacs.umd.edu
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 10
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    Engineering modified Bt toxins to counter insect resistance (2007)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 2007-11-03
    Description: The evolution of insect resistance threatens the effectiveness of Bacillus thuringiensis (Bt) toxins that are widely used in sprays and transgenic crops. Resistance to Bt toxins in some insects is linked with mutations that disrupt a toxin-binding cadherin protein. We show that susceptibility to the Bt toxin Cry1Ab was reduced by cadherin gene silencing with RNA interference in Manduca sexta, confirming cadherin's role in Bt toxicity. Native Cry1A toxins required cadherin to form oligomers, but modified Cry1A toxins lacking one alpha-helix did not. The modified toxins killed cadherin-silenced M. sexta and Bt-resistant Pectinophora gossypiella that had cadherin deletion mutations. Our findings suggest that cadherin promotes Bt toxicity by facilitating toxin oligomerization and demonstrate that the modified Bt toxins may be useful against pests resistant to standard Bt toxins.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Soberon, Mario -- Pardo-Lopez, Liliana -- Lopez, Idalia -- Gomez, Isabel -- Tabashnik, Bruce E -- Bravo, Alejandra -- 1R01 AI066014/AI/NIAID NIH HHS/ -- New York, N.Y. -- Science. 2007 Dec 7;318(5856):1640-2. Epub 2007 Nov 1.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Instituto de Biotecnologia, Universidad Nacional Autonoma de Mexico, Apartado Postal 510-3, Cuernavaca 62250, Morelos, Mexico. mario@ibt.unam.mx〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/17975031" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Bacterial Proteins/chemistry/*genetics/metabolism/*toxicity ; Bacterial Toxins/chemistry/*genetics/metabolism/*toxicity ; Cadherins/genetics/metabolism ; Endotoxins/chemistry/*genetics/metabolism/*toxicity ; Genetic Engineering ; Hemolysin Proteins/chemistry/*genetics/metabolism/*toxicity ; *Insecticide Resistance ; Larva ; *Manduca/genetics/metabolism ; *Moths/genetics/metabolism ; Mutation ; *Pest Control, Biological ; RNA Interference
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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