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<dc:title>Cloud-based solutions supporting data and knowledge integration in bioinformatics</dc:title>
<dc:creator>MILIA, GABRIELE</dc:creator>
<dc:subject>applicazioni cloud</dc:subject>
<dc:subject>bioinformatica</dc:subject>
<dc:subject>bioinformatics</dc:subject>
<dc:subject>biomedial data exploration</dc:subject>
<dc:subject>cloud applications</dc:subject>
<dc:subject>cloud computing</dc:subject>
<dc:subject>collaborative knowledge management</dc:subject>
<dc:subject>data integration</dc:subject>
<dc:subject>integrazione dati</dc:subject>
<dc:subject>random forests</dc:subject>
<dc:subject>Settore INF/01 - Informatica</dc:subject>
<dc:description>In recent years, computer advances have changed the way the science progresses and have&#xd;
boosted studies in silico; as a result, the concept of “scientific research” in bioinformatics&#xd;
has quickly changed shifting from the idea of a local laboratory activity towards Web&#xd;
applications and databases provided over the network as services. Thus, biologists have&#xd;
become among the largest beneficiaries of the information technologies, reaching and&#xd;
surpassing the traditional ICT users who operate in the field of so-called "hard science"&#xd;
(i.e., physics, chemistry, and mathematics). Nevertheless, this evolution has to deal with&#xd;
several aspects (including data deluge, data integration, and scientific collaboration, just to&#xd;
cite a few) and presents new challenges related to the proposal of innovative approaches in&#xd;
the wide scenario of emergent ICT solutions.&#xd;
This thesis aims at facing these challenges in the context of three case studies, being&#xd;
each case study devoted to cope with a specific open issue by proposing proper solutions in&#xd;
line with recent advances in computer science.&#xd;
The first case study focuses on the task of unearthing and integrating information from&#xd;
different web resources, each having its own organization, terminology and data formats in&#xd;
order to provide users with flexible environment for accessing the above resources and&#xd;
smartly exploring their content. The study explores the potential of cloud paradigm as an&#xd;
enabling technology to severely curtail issues associated with scalability and performance&#xd;
of applications devoted to support the above task. Specifically, it presents Biocloud Search&#xd;
EnGene (BSE), a cloud-based application which allows for searching and integrating&#xd;
biological information made available by public large-scale genomic repositories. BSE is&#xd;
publicly available at: http://biocloud-unica.appspot.com/.&#xd;
&#xd;
The second case study addresses scientific collaboration on the Web with special focus&#xd;
on building a semantic network, where team members, adequately supported by easy&#xd;
access to biomedical ontologies, define and enrich network nodes with annotations derived&#xd;
from available ontologies. The study presents a cloud-based application called&#xd;
Collaborative Workspaces in Biomedicine (COWB) which deals with supporting users in&#xd;
the construction of the semantic network by organizing, retrieving and creating&#xd;
connections between contents of different types. Public and private workspaces provide an&#xd;
accessible representation of the collective knowledge that is incrementally expanded.&#xd;
COWB is publicly available at: http://cowb-unica.appspot.com/.&#xd;
Finally, the third case study concerns the knowledge extraction from very large datasets.&#xd;
The study investigates the performance of random forests in classifying microarray data. In&#xd;
particular, the study faces the problem of reducing the contribution of trees whose nodes&#xd;
are populated by non-informative features. Experiments are presented and results are then&#xd;
analyzed in order to draw guidelines about how reducing the above contribution.&#xd;
With respect to the previously mentioned challenges, this thesis sets out to give two&#xd;
contributions summarized as follows. First, the potential of cloud technologies has been&#xd;
evaluated for developing applications that support the access to bioinformatics resources&#xd;
and the collaboration by improving awareness of user's contributions and fostering users&#xd;
interaction. Second, the positive impact of the decision support offered by random forests&#xd;
has been demonstrated in order to tackle effectively the curse of dimensionality.</dc:description>
<dc:date>2015-05-25</dc:date>
<dc:type>info:eu-repo/semantics/doctoralThesis</dc:type>
<dc:identifier>http://hdl.handle.net/11584/266783</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>numberofpages:96</dc:relation>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:publisher>Università degli Studi di Cagliari</dc:publisher>
<dc:rights>license:Non specificato</dc:rights>
</oai_dc:dc></metadata></record></GetRecord></OAI-PMH>