Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Antonella Travaglione"'
Autor:
Paolo Uva, Angela Orecchia, Francesca Cianfarani, Eugenia Piccinni, Giovanna Zambruno, Barbara Bellei, Antonella Travaglione, Michela Di Salvio, Andrea Conti, Teresa Odorisio, Daniele Castiglia, Giovanni Di Zenzo
Publikováno v:
Human Molecular Genetics. 23:3907-3922
Recessive dystrophic epidermolysis bullosa (RDEB) is a genodermatosis characterized by fragile skin forming blisters that heal invariably with scars. It is due to mutations in the COL7A1 gene encoding type VII collagen, the major component of anchori
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d93d12e0dcd2b5c2963fbb0a408abb8
https://doi.org/10.1093/hmg/ddu102
https://doi.org/10.1093/hmg/ddu102
Publikováno v:
Journal of Computational Biology. 18:81-96
Many studies and applications in the post-genomic era have been devoted to analyze complex biological systems by computational inference methods. We propose to apply manifold learning methods to protein-protein interaction networks (PPIN). Despite th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9faad9357e83e2566d37a255ff319b5b
https://doi.org/10.1089/cmb.2009.0258
https://doi.org/10.1089/cmb.2009.0258
Publikováno v:
Gene. 530(2)
Translational cancer genomics research aims to ensure that experimental knowledge is subject to computational analysis, and integrated with a variety of records from omics and clinical sources. The data retrieval from such sources is not trivial, due
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ab74a3232a65923f32dc52286053dc1
https://pubmed.ncbi.nlm.nih.gov/23928109
https://pubmed.ncbi.nlm.nih.gov/23928109
Publikováno v:
Statistical and Machine Learning Approaches for Network Analysis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::75e13531926a350a39f2f26d7f6bbee7
https://doi.org/10.1002/9781118346990.ch4
https://doi.org/10.1002/9781118346990.ch4
Publikováno v:
Statistical Applications in Genetics and Molecular Biology. 10
Inference methods applied to biological networks suffer from a main criticism: as the latter reflect associations measured under static conditions, an evaluation of the underlying modular organization can be biologically meaningful only if the dynami
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::89eabb755aa8b06a2550f8b435e65989
https://doi.org/10.2202/1544-6115.1657
https://doi.org/10.2202/1544-6115.1657
Autor:
Andrea Pinna, Antonella Travaglione, Paolo Uva, Gianluigi Zanetti, Gianmauro Cuccuru, Giorgio Fotia, Nicola Soranzo, Andrea Sbardellati, Massimiliano Orsini
Publikováno v:
Bioinformatics
Summary: End-to-end next-generation sequencing microbiology data analysis requires a diversity of tools covering bacterial resequencing, de novo assembly, scaffolding, bacterial RNA-Seq, gene annotation and metagenomics. However, the construction of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::200d8301369c5b19e718262ba9d0740a
https://doi.org/10.1093/bioinformatics/btu135
https://doi.org/10.1093/bioinformatics/btu135
Autor:
Gautam Chaurasia, Antonella Travaglione, Matthias E. Futschik, Elisabetta Marras, Enrico Capobianco
Publikováno v:
Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
BMC Systems Biology
BMC Systems Biology, Vol 4, Iss 1, p 102 (2010)
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
BMC Systems Biology
BMC Systems Biology, Vol 4, Iss 1, p 102 (2010)
Background The integration of protein-protein interaction networks derived from high-throughput screening approaches and complementary sources is a key topic in systems biology. Although integration of protein interaction data is conventionally perfo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::56262d688ffe8bad5bc48b19b26b9dbf
http://edoc.mdc-berlin.de/11236/1/11236oa.pdf
http://edoc.mdc-berlin.de/11236/1/11236oa.pdf
Publikováno v:
Statistical Applications in Genetics and Molecular Biology. 9
Inferring the structure of networks usually involves the attempt of retrieving their modular organization and knowing its possible interpretation, while quantifying the involved computational complexity through the methods and algorithms to be used.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8ed4e5383a4dc3b8f8c6150d12e04ad8
https://doi.org/10.2202/1544-6115.1523
https://doi.org/10.2202/1544-6115.1523