Search results for "informatics"

showing 10 items of 2542 documents

Insects and fungi: ecological interactions and functional biodiversity

BioinformaticBark beetleMetabarcoding; Bioinformatics; Bactrocera oleae; Bark beetles; Ambrosia beetles; Aphids; Aboveground-belowground interactionsSettore AGR/11 - Entomologia Generale E ApplicataBactrocera oleaeMetabarcodingAboveground-belowground interactionsSettore AGR/12 - Patologia VegetaleAphidAmbrosia beetle
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Mapreduce in computational biology - A synopsis

2017

In the past 20 years, the Life Sciences have witnessed a paradigm shift in the way research is performed. Indeed, the computational part of biological and clinical studies has become central or is becoming so. Correspondingly, the amount of data that one needs to process, compare and analyze, has experienced an exponential growth. As a consequence, High Performance Computing (HPC, for short) is being used intensively, in particular in terms of multi-core architectures. However, recently and thanks to the advances in the processing of other scientific and commercial data, Distributed Computing is also being considered for Bioinformatics applications. In particular, the MapReduce paradigm, to…

BioinformaticSpark0301 basic medicineSettore INF/01 - InformaticaBioinformaticsProcess (engineering)Computer scienceComputer Science (all)Computational biologybioinformatics; distributed computing; hadoop; MapReduce; spark; computer science (all)Supercomputercomputer.software_genreDistributed computing03 medical and health sciences030104 developmental biologyExponential growthHadoopParadigm shiftMiddleware (distributed applications)Spark (mathematics)MapReducecomputer
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Mapreduce in computational biology via hadoop and spark

2017

Bioinformatics has a long history of software solutions developed on multi-core computing systems for solving computational intensive problems. This option suffer from some issues solvable by shifting to Distributed Systems. In particular, the MapReduce computing paradigm, and its implementations, Hadoop and Spark, is becoming increasingly popular in the Bioinformatics field because it allows for virtual-unlimited horizontal scalability while being easy-to-use. Here we provide a qualitative evaluation of some of the most significant MapReduce bioinformatics applications. We also focus on one of these applications to show the importance of correctly engineering an application to fully exploi…

BioinformaticSparkSettore INF/01 - InformaticaExploitbusiness.industryComputer scienceBioinformaticsDistributed computingScalabilityAlgorithm engineeringField (computer science)Distributed computingSoftwareAlgorithm engineering; Bioinformatics; Distributed computing; Hadoop; MapReduce; Scalability; SparkHadoopSpark (mathematics)ScalabilityData-intensive computingMapReducebusinessImplementationAlgorithm engineering
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Gene ontology-based annotation and comparative analysis of proteins extracted from proteomics of 100 breast cancer patients.

2009

Background: Current clinical parameters for breast cancer diagnosis and therapy are: tumour size, axillary lymph node status, histological grading and presence or absence of metastases. Prognostic/predictive properties, such as oestrogen and progesterone receptor status, and human epidermal growth factor receptor (HER-2/neu) status are currently used for therapeutic decision. Conversely, it is now emerging that the number of genetic mutations and epigenetic deregulations in cancer is far more higher than previously thought. Therefore, proteomic screening for differential protein expression in subsets of tumor samples is an essential tool for generating data bases and biomarker discovery. Th…

Bioinformatics Resourcesbreast cancer patientSettore BIO/06 - Anatomia Comparata E Citologiaproteomic
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PathVisio Analysis: An Application Targeting the miRNA Network Associated with the p53 Signaling Pathway in Osteosarcoma

2021

MicroRNAs (miRNAs) are small single-stranded, non-coding RNA molecules involved in the pathogenesis and progression of cancer, including osteosarcoma. We aimed to clarify the pathways involving miRNAs using new bioinformatics tools. We applied WikiPathways and PathVisio, two open-source platforms, to analyze miRNAs in osteosarcoma using miRTar and ONCO.IO as integration tools. We found 1298 records of osteosarcoma papers associated with the word "miRNA". In osteosarcoma patients with good response to chemotherapy, miR-92a, miR- 99b, miR-193a-5p, and miR-422a expression is increased, while miR-132 is decreased. All identified miRNAs seem to be centered on the TP53 network. This is the first …

Bioinformatics Bone tumor Cancer CarcinogenesisMiRNA Oncology Osteosarcoma p53P53 Signaling PathwaymicroRNACancer researchmedicineOsteosarcomaGeneral MedicineBiologymedicine.disease
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IP6K gene identification by tag search

2010

Bioinformatics Motif extraction String analysis
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IP6K gene identification in plant cells via tag discovery

2010

Bioinformatics Motif extraction String analysis
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IP6K gene identification in plant genomes by tag searching

2011

Abstract Background Plants have played a special role in inositol polyphosphate (IP) research since in plant seeds was discovered the first IP, the fully phosphorylated inositol ring of phytic acid (IP6). It is now known that phytic acid is further metabolized by the IP6 Kinases (IP6Ks) to generate IP containing pyro-phosphate moiety. The IP6K are evolutionary conserved enzymes identified in several mammalian, fungi and amoebae species. Although IP6K has not yet been identified in plant chromosomes, there are many clues suggesting its presences in vegetal cells. Results In this paper we propose a new approach to search for the plant IP6K gene, that lead to the identification in plant genome…

Bioinformatics Motif extraction String analysisGeneticsMitochondrial DNAOryza sativaNuclear genebiologyNucleic acid sequencefood and beveragesChromosomeGeneral Medicinebiology.organism_classificationGenomeGeneral Biochemistry Genetics and Molecular BiologyProceedingsArabidopsis thalianaGeneBMC Proceedings
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Pattern Discovery In Biosequences: From Simple To Complex Patterns

2007

Bioinformatics Pattern Discovery String Analysis
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Singling out functional similarities in graph databases

2008

Bioinformatics network analysis
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