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020			_a9783030571733
024	7		_a10.1007/978-3-030-57173-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _erda _dES-MaUEC
050		4	_aR856 _b2021 EB
245	0	0	_aRecent Advances in Biological Network Analysis : _bComparative Network Analysis and Network Module Detection _cedited by Byung-Jun Yoon, Xiaoning Qian
250			_aFirst edition 2021
264		1	_aCham _bSpringer International Publishing _c2021
300			_a1 recurso en línea (XII, 217 páginas) _b42 ilustraciones, 29 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de trexto _bPDF _2rda
490	0		_aBiomedical and Life Sciences (SpringerNature-11642)
490	0		_aBiomedical and Life Sciences (R0) (SpringerNature-43708)
505	0		_aChapter 1: Global Alignment of PPI Networks -- Chapter 2: Integrated Network-Based Computational Analysis for Drug Development -- Chapter 3: Effective Random Walk Models for Comparative Network Analysis -- Chapter 4: Computational Methods for Protein-Protein Interaction Network Alignment -- Chapter 5: Network Propagation for the Analysis of Multi_Omics Data -- Chapter 6: Motifs in Biological Networks -- Chapter 7: Bio Fabric Visualization of Network Alignments -- Chapter 8: Module Identification of Biological Networks via Graph Partition -- Chapter 9: Network Module Detection to Decipher the Heterogeneity of Cancer Mutations.
520	3		_aThis book reviews recent advances in the emerging field of computational network biology with special emphasis on comparative network analysis and network module detection. The chapters in this volume are contributed by leading international researchers in computational network biology and offer in-depth insight on the latest techniques in network alignment, network clustering, and network module detection. Chapters discuss the advantages of the respective techniques and present the current challenges and open problems in the field. Recent Advances in Biological Network Analysis: Comparative Network Analysis and Network Module Detection will serve as a great resource for graduate students, academics, and researchers who are currently working in areas relevant to computational network biology or wish to learn more about the field. Data scientists whose work involves the analysis of graphs, networks, and other types of data with topological structure or relations can also benefit from the book's insights. .
988			_aSpringer_BiomedLife_2021
650		7	_2embne _9143820 _aIngeniería biomédica
700	1		_aYoon, Byung-Jun _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aQian, Xiaoning _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9783030571726
776	0	8	_iPrinted edition: _z9783030571740
776	0	8	_iPrinted edition: _z9783030571757
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-57173-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b03/2021 _dz _ek _zSI