LEADER 03206nam 2200589Ia 450 001 9910828877703321 005 20240313222620.0 010 $a1-281-96817-X 010 $a9786611968175 010 $a981-281-478-7 035 $a(CKB)1000000000554952 035 $a(EBL)1193653 035 $a(SSID)ssj0000301558 035 $a(PQKBManifestationID)12096924 035 $a(PQKBTitleCode)TC0000301558 035 $a(PQKBWorkID)10263559 035 $a(PQKB)11584129 035 $a(MiAaPQ)EBC1193653 035 $a(WSP)00006403 035 $a(Au-PeEL)EBL1193653 035 $a(CaPaEBR)ebr10688086 035 $a(CaONFJC)MIL196817 035 $a(OCoLC)318879610 035 $a(EXLCZ)991000000000554952 100 $a20090306d2008 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aLecture notes on computational structural biology /$fZhijun Wu 205 $a1st ed. 210 $aSingapore ;$aHackensack, NJ $cWorld Scientific$dc2008 215 $a1 online resource (244 p.) 300 $aDescription based upon print version of record. 311 $a981-270-589-9 320 $aIncludes bibliographical references and index. 327 $a1. Introduction. 1.1. Protein structure. 1.2. Structure determination. 1.3. Dynamics simulation. 1.4. The myth of protein folding -- 2. X-ray crystallography computing. 2.1. The phase problem. 2.2. Least squares solutions. 2.3. Entropy maximization. 2.4. Indirect methods -- 3. NMR structure determination. 3.1. Nuclear magnetic resonance. 3.2. Distance geometry. 3.3. Distance-based modeling. 3.4. Structural analysis -- 4. Potential energy minimization. 4.1. Potential energy function. 4.2. Local optimization. 4.3. Global optimization. 4.4. Energy transformation -- 5. Molecular dynamics simulation. 5.1. Equations of motion. 5.2. Initial-value problem. 5.3. Boundary-value problem. 5.4. Normal mode analysis -- 6. Knowledge-based protein modeling. 6.1. Sequence/structural alignment. 6.2. Fold recognition/inverse folding. 6.3. Knowledge-based structural refinement. 6.4. Structural computing and beyond. 330 $aWhile the field of computational structural biology or structural bioinformatics is rapidly developing, there are few books with a relatively complete coverage of such diverse research subjects studied in the field as X-ray crystallography computing, NMR structure determination, potential energy minimization, dynamics simulation, and knowledge-based modeling. This book helps fill the gap by providing such a survey on all the related subjects. Comprising a collection of lecture notes for a computational structural biology course for the Program on Bioinformatics and Computational Biology at Iow 606 $aComputational biology 606 $aStructural bioinformatics 615 0$aComputational biology. 615 0$aStructural bioinformatics. 676 $a572.80285 700 $aWu$b Zhijun$f1956-$01639348 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910828877703321 996 $aLecture notes on computational structural biology$93982267 997 $aUNINA