000			06207cam a2200505Ii 4500
001			95949
003			ES-MaUEC
005			20230102112730.0
006			m o d
007			cr cnu|||unuuu
008			170508s2017 si a ob 000 0 eng d
020			_a9789811018572 _q(electronic bk.)
020			_a981101857X _q(electronic bk.)
020			_z9789811018565 _q(print)
020			_z9811018561
040			_aN$T _cN$T _dGW5XE _dEBLCP _dN$T _dYDX _dOCLCF _dUAB _dESU _dIOG _dSTF _dCOO _dU3W _dES-MaUEC _bspa
050		4	_aQH324.2 _bB565 2017 EB
245	0	0	_aBioinformatics -- a student's companion _cKalibulla Syed Ibrahim, Guruswami Gurusubramanian, Zothansanga, Ravi Prakash Yadav, Nachimuthu Senthil Kumar, Shunmugiah Karutha Pandian, Probodh Borah, Surender Mohan.
264		1	_aSingapore _bSpringer _c2017.
300			_a1 recurso en línea (xv, 283 páginas) _bilustraciones
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
500			_aSpringerLink _bSpringer Biomedical and Life Sciences eBooks 2017 English+International
504			_aIncluye referencias bibliográficas
505	0		_aForeword; Preface; Contents; About the Authors; 1 Nucleotide Analysis; 1.1 Sequence Retrieval; 1.2 Primer Designing; 1.3 Designing Degenerate Primers; 1.4 Reading of Sequence Trace Files Using Finch TV; 1.5 Troubleshooting DNA Sequencing Problems; 1.6 Editing Sequence Data; 1.7 Sequence Assembly-CAP3 Program; 1.8 Checking for Vector Contamination; 1.9 Restriction Mapping Using NEBcutter; 1.10 Gene Prediction Using ORF Finder (Open Reading Frame Finder); 1.11 Gene Prediction Using FGENESB; 1.12 Dot-Plot; 1.13 Global Sequence Alignment; 1.14 Local Sequence Alignment
505	8		_a1.15 Basic Local Alignment Search Tool (BLAST)-Nucleotide BLAST1.16 Interpreting BLAST Result; 1.17 Multiple Sequence Alignment: T-Coffee for Small Alignments; 1.18 Multiple Sequence Alignment-MUSCLE for Medium Alignments; 1.19 Multiple Sequence Alignment-MAFFT for Large Alignments; 1.20 Multiple Sequence Alignment and Phylogenetic Analysis Using MEGA; 2 DNA Marker Analysis; 2.1 Genetic Analysis Using NTSYSpc (Numerical Taxonomy System); 2.2 Principal Coordinate Analysis (PCOORDA) Using NTSYSpc; 2.3 Population Genetic Analysis Using PowerMarker
505	8		_a2.4 Dissimilarity Analysis-DARwin5 (Dissimilarity Analysis and Representation for Windows)3 RNA Analysis; 3.1 Predicting RNA Secondary Structure; 3.2 Finding Repeats; 4 Protein Sequence Analysis; 4.1 Protein Sequence Retrieval from UniProtKB; 4.2 Visualization of Features in a Multiple Sequence Alignment; 4.3 Predicting Signal Peptides in Proteins Using SignalP 4.1 Server; 4.4 Predicting Transmembrane Segments and Signal Peptides in Proteins Using Phobius; 4.5 Predicting Subcellular Location Using TargetP; 4.6 Protein BLAST (blastp); 4.7 Position-Specific Iterated (PSI)-BLAST
505	8		_a4.8 Creating Pattern from Alignment4.9 Pattern-Hit Initiated (PHI)-BLAST; 4.10 Domain Enhanced Lookup Time Accelerated-BLAST (DELTA-BLAST); 5 Protein Structure Analysis; 5.1 Protein Primary Structure Analysis-ProtParam; 5.2 Protein Secondary Structure Prediction; 5.2.1 Secondary Structure Prediction Using SOPMA; 5.2.2 Secondary Structure Prediction Using PSIPRED; 5.3 Protein Tertiary Structure Prediction by Homology Modelling; 5.3.1 Homology Modelling Using SwissModel; 5.3.2 Protein Tertiary Structure Prediction by Threading (Fold Recognition); 5.4 Protein Tertiary Structure Analysis
505	8		_a5.4.1 RAMPAGE5.4.2 Protein Structure Analysis Using SAVeS; 5.5 Protein Structure Visualization; 5.5.1 RasMol; 5.5.2 PyMol; 5.6 Protein Structure Alignment/Superimpose Using SuperPose; 5.7 Protein Cleft Analysis; 6 Protein-Ligand Interactions; 6.1 Protein-Ligand Docking Using AutoDock4.1 and MGLTools; 6.2 Protein-Protein Docking Using ClusPro2.0; Appendix: Online Resources on Bioinformatics; References
520	3		_aThis manual offers a stand-alone reading companion, unique in simplifying the practical components of Bioinformatics in a unique and user-friendly manner. It covers the practical component of syllabi used at most leading universities and discusses the most extensively used tools and methodologies in Bioinformatics. Research in the biological sciences has made tremendous strides in recent years due in part to the increased automation in data generation. At the same time, storing, managing and interpreting huge volumes of data has become one of the most challenging tasks for scientists. These two aspects have ultimately necessitated the application of computers, giving rise to a highly interdisciplinary discipline?Bioinformatics. Despite the richness of bioinformatics resources and methods, the exposure of life sciences undergraduates and postgraduates to bioinformatics is extremely limited. Though the internet offers various tools for free, and provides guides for using them, it fails to help users interpret the processed data. Moreover, most sites fail to update their help pages to accommodate software upgrades. Though the market is flooded with books discussing the theoretical concepts in Bioinformatics, a manual of this kind is rarely found. The content developed to meet the needs of readers from diverse background and to incorporate the syllabi of undergraduate and postgraduate courses at various universities.
588	0		_aOnline resource; title from PDF title page (SpringerLink, viewed May 12, 2017).
650		7	_aBioinformática _2embne _0(OCoLC)fst00832181 _0LocalZ _9160489
700	0		_aZothansanga, _eautor
700	1		_aBorah, Probodh, _eautor
700	1		_aGurusubramanian, Guruswami, _eautor
700	1		_aIbrahim, Kalibulla Syed, _eautor
700	1		_aKumar, Nachimuthu Senthil, _eautor
700	1		_aMohan, Surender, _eautor
700	1		_aPandian, Shunmugiah Karutha, _eautor
700	1		_aYadav, Ravi Prakash, _eautor
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=http://link.springer.com/10.1007/978-981-10-1857-2 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
988			_aEBOOK, EBSPRINGER_2017D
998			_b02/2018 _dz _e- _zSI
999			_c95949 _d95949 _x1