000 04065cam a2200721Ia 4500
001 ocn851153926
003 OCoLC
005 20171106100209.0
006 m o d
007 cr cnu|||unuuu
008 130628s2013 gw ob 001 0 eng d
016 7 _a016300421
_2Uk
020 _a9783527670475
_q(electronic bk.)
020 _a3527670475
_q(electronic bk.)
020 _a1299701469
_q(ebk)
020 _a9781299701465
_q(ebk)
020 _a9783527670499
_q(mobi)
020 _a3527670491
_q(mobi)
020 _a9783527670468
020 _a3527670467
020 _a352733291X
_q(hbk.)
020 _a9783527332915
_q(hbk.)
020 _z9783527332915
020 _z3527670467
029 1 _aAU@
_b000051817004
029 1 _aDEBBG
_bBV041908928
029 1 _aDEBSZ
_b452516447
029 1 _aDKDLA
_b820120-katalog:000732191
029 1 _aNLGGC
_b363611576
029 1 _aNZ1
_b15497581
029 1 _aDEBBG
_bBV043396045
035 _a(OCoLC)851153926
_z(OCoLC)857446982
_z(OCoLC)958541141
_z(OCoLC)961695972
_z(OCoLC)962729852
040 _aIDEBK
_beng
_epn
_cIDEBK
_dEBLCP
_dMHW
_dCUS
_dN$T
_dCUI
_dUKMGB
_dNOC
_dOCLCO
_dCOO
_dYDXCP
_dE7B
_dOCLCF
_dGGVRL
_dOCLCO
_dOCLCQ
_dOCLCO
_dCDX
_dIEDUB
_dDEBBG
_dDEBSZ
_dOCLCQ
_dLOA
_dK6U
049 _aMAIN
050 4 _aQH324
072 7 _aSCI
_x008000
_2bisacsh
082 0 4 _a574.028
_223
245 0 0 _aAdvances in network complexity /
_cedited by Matthias Dehmer, Abbe Mowshowitz, and Frank Emmert-Streib.
_h[electronic resource]
260 _aWeinheim, Germany :
_bWiley-Blackwell,
_c[2013]
300 _a1 online resource (xiv, 293 pages .).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aQuantitative and network biology ;
_vvolume 4
504 _aIncludes bibliographical references and index.
505 0 _a1. Functional complexity based on topology -- 2. Connections between artificial intelligence and conputational complexity and the complexity of graphs -- 3. Selection-based estimates of complexity unravel some mechanisms and selective pressures underlying the evolution of complexity in artificial networks -- 4. Three types of network complexity pyramid -- 5. Computational complexity of graphs -- 6. The linear complexity of a graph -- 7. Kirchhoff's matrix-tree theorem revisited: counting spanning trees with the quantum relative entropy -- 8. Dimension measure for complex networks -- 9. Information-based complexity of networks -- 10. Thermodynamic depth in undirected and directed networks -- 11. Circumscribed complexity in ecological networks -- 12. Metros as biological systems complexity in small real-life networks.
520 _aA well-balanced overview of mathematical approaches to describe complex systems, ranging from chemical reactions to gene regulation networks, from ecological systems to examples from social sciences. Matthias Dehmer and Abbe Mowshowitz, a well-known pioneer in the field, co-edit this volume and are careful to include not only classical but also non-classical approaches so as to ensure topicality. Overall, a valuable addition to the literature and a must-have for anyone dealing with complex systems.
588 0 _aOnline resource; title from PDF title page (Wiley, viewed July 24, 2013).
650 0 _aComputational biology.
650 0 _aBiomedical engineering
_xMathematical models.
650 7 _aSCIENCE
_xLife Sciences
_xBiology.
_2bisacsh
650 7 _aBiomedical engineering
_xMathematical models.
_2fast
_0(OCoLC)fst00832575
650 7 _aComputational biology.
_2fast
_0(OCoLC)fst00871990
655 4 _aElectronic books.
655 7 _aElectronic books.
_2local
700 1 _aDehmer, Matthias,
_d1968-
_eeditor.
700 1 _aMowshowitz, Abbe,
_eeditor.
700 1 _aEmmert-Streib, Frank,
_eeditor.
776 0 8 _iPrint version:
_z9783527332915
_w(UK-RwCLS)352733291X
830 0 _aQuantitative and network biology ;
_vv. 4.
856 4 0 _uhttp://onlinelibrary.wiley.com/book/10.1002/9783527670468
_zWiley Online Library
942 _2ddc
_cBK
999 _c206858
_d206858