000 02242nam a22003258i 4500
001 CR9781108377706
003 UkCbUP
005 20200124160156.0
006 m|||||o||d||||||||
007 cr||||||||||||
008 170503s2019||||enk o ||1 0|eng|d
020 _a9781108377706 (ebook)
020 _z9781108432238 (paperback)
040 _aUkCbUP
_beng
_erda
_cUkCbUP
050 0 0 _aR858
_b.A469 2019
082 0 0 _a610.285
_223
245 0 0 _aAnalyzing network data in biology and medicine :
_ban interdisciplinary textbook for biological, medical and computational scientists /
_cedited and authored by Nataša Pržulj.
264 1 _aCambridge :
_bCambridge University Press,
_c2019.
300 _a1 online resource (xiv, 632 pages) :
_bdigital, PDF file(s).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
500 _aTitle from publisher's bibliographic system (viewed on 13 Mar 2019).
520 _aThe increased and widespread availability of large network data resources in recent years has resulted in a growing need for effective methods for their analysis. The challenge is to detect patterns that provide a better understanding of the data. However, this is not a straight forward task because of the size of the data sets and the computer power required for the analysis. The solution is to devise methods for approximately answering the questions posed, and these methods will vary depending on the data sets under scrutiny. This cutting-edge text introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, before discussing the thought processes and creativity involved in the analysis of large-scale biological and medical data sets, using a wide range of real-life examples. Bringing together leading experts, this text provides an ideal introduction to and insight into the interdisciplinary field of network data analysis in biomedicine.
650 0 _aMedical informatics
_xData processing.
650 0 _aBioinformatics.
700 1 _aPržulj, Nataša,
_eeditor.
776 0 8 _iPrint version:
_z9781108432238
856 4 0 _uhttps://doi.org/10.1017/9781108377706
999 _c514488
_d514486