000 03006cam a2200313 i 4500
001 17612560
003 ISI Library, Kolkata
005 20141126123023.0
008 130204s2013 flua b 001 0 eng
020 _a9781584884637 (hardback)
040 _aISI Library
082 0 0 _a571.7
_223
_bR252
100 1 _aRaval, Alpan.
245 1 0 _aIntroduction to biological networks /
_cAlpan Raval and Animesh Ray.
260 _aBoca Raton :
_bCRC Press,
_cc2013.
300 _axiii, 321 p. :
_billustrations ;
_c25 cm.
490 0 _aChapman & Hall/CRC mathematical & computational biology series
504 _aIncludes bibliographical references and index.
505 _a1. The living interactome -- 2. Experimental inference of interactions -- 3. Prediction of physical interactions -- 4. Metabolic networks and genetic interactions -- 5. Testing inferred networks -- 6. Small model networks -- 7. Tractable models of large networks -- 8. Network modularity and robustness -- 9. Networks and disease-- References-- Index--
520 _a"Preface In the 1940s and 1950s, biology was transformed by physicists and physical chemists, who employed simple yet powerful concepts and engaged the powers of genetics to infer mechanisms of biological processes. The biological sciences borrowed from the physical sciences the notion of building intuitive, testable, and physically realistic models by reducing the complexity of biological systems to the components essential for studying the problem at hand. Molecular biology was born. A similar migration of physical scientists and of methods of physical sciences into biology has been occurring in the decade following the complete sequencing of the human genome, whose discrete character and similarity to natural language has additionally facilitated the application of the techniques of modern computer science. Furthermore, the vast amount of genomic data spawned by the sequencing projects has led to the development and application of statistical methods for making sense of this data. The sheer amount of data at the genome scale that is available to us today begs for descriptions that go beyond simple models of the function of a single gene to embrace a systemlevel understanding of large sets of genes functioning in unison. It is no longer sufficient to understand how a single gene mutation causes a change in its product's biochemical function, although this is in many cases still an important problem. It is now possible to address how the consequences of a mutation might reverberate through the interconnected system of genes and their products within the cell"--
650 0 _aBiological systems
_xMathematical models.
650 0 _aSystems biology
_xMathematical models.
650 0 _aComputational biology.
650 7 _aMATHEMATICS / Probability & Statistics / General.
650 7 _aCOMPUTERS / Programming / Algorithms.
650 7 _aSCIENCE / Biotechnology.
700 1 _aRay, Animesh.
942 _2ddc
_cBK
999 _c416239
_d416239