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020 _a9781849961042
_99781849961042
024 7 _a10.1007/9781849961042
_2doi
035 _avtls000344627
039 9 _a201509030424
_bVLOAD
_c201405050310
_dVLOAD
_y201402061302
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aQH324.2-324.25
100 1 _aAxelson-Fisk, Marina.
_eautor
_9322286
245 1 0 _aComparative Gene Finding :
_bModels, Algorithms and Implementation /
_cby Marina Axelson-Fisk.
264 1 _aLondon :
_bSpringer London,
_c2010.
300 _axv, 304 páginas
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aComputational Biology,
_x1568-2684 ;
_v11
500 _aSpringer eBooks
505 0 _aSingle Species Gene Finding -- Sequence Alignment -- Comparative Gene Finding -- Gene Structure Submodels -- Parameter Training -- Implementation of a Comparative Gene Finder.
520 _aComparative genomics is an emerging field, which is being fed by an explosion in the number of possible biological sequences. This has led to an immense demand for faster, more efficient and more robust computer algorithms to analyze this large amount of data. This unique text/reference describes the state of the art in computational gene finding, with a particular focus on comparative approaches. Providing both an overview of the various methods that are applied in the field, and a concise guide on how computational gene finders are built, the book covers a broad range of topics from probability theory, statistics, information theory, optimization theory and numerical analysis. The text assumes the reader has some background in bioinformatics, especially in mathematics and mathematical statistics. A basic knowledge of analysis, probability theory and random processes would also aid the reader. Topics and features: Describes how algorithms and sequence alignments can be combined to improve the accuracy of gene finding Introduces the basic biological terms and concepts in genetics, and provides an historical overview of algorithm development Explores the gene features most commonly captured by a computational gene model, and describes the most important sub-models used Discusses the algorithms most commonly used for single-species gene finding Investigates approaches to pairwise and multiple sequence alignments Explains the basics of parameter training, covering a number of the different parameter estimation and optimization techniques commonly used in gene finding Illustrates how to implement a comparative gene finder, explaining the different steps and various accuracy assessment measures used to debug and benchmark the software A useful text for postgraduate students, this book provides valuable insights and examples for researchers wishing to enter the field quickly. In addition to the specific focus on the algorithmic details surrounding computational gene finding, readers obtain an introduction to the fundamentals of computational biology and biological sequence analysis, as well as an overview of the important mathematical and statistical applications in bioinformatics. Dr. Marina Axelson-Fisk is an Associate Professor at the Department of Mathematical Sciences of Chalmers University of Technology, Gothenburg, Sweden.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9781849961035
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-84996-104-2
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999 _c291137
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