Cantitate/Preț
Produs

Computational Biology

Editat de Alona S. Russe
en Limba Engleză Hardback – 13 aug 2009
Computational biology involves the use of techniques including applied mathematics, informatics, statistics, computer science, artificial intelligence, chemistry, and biochemistry to solve biological problems usually on the molecular level. The core principle of these techniques is using computing resources in order to solve problems on scales of magnitude far too great for human discernment. Research in computational biology often overlaps with systems biology. Major research efforts in the field include sequence alignment, gene finding, genome assembly, protein structure alignment, protein structure prediction, prediction of gene expression and protein-protein interactions, and the modeling of evolution.
Citește tot Restrânge

Preț: 97223 lei

Preț vechi: 132233 lei
-26% Nou

Puncte Express: 1458

Preț estimativ în valută:
18607 19374$ 15725£

Carte disponibilă

Livrare economică 18 februarie-04 martie

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9781606920404
ISBN-10: 1606920405
Pagini: 441
Ilustrații: colour photos, tables & charts
Dimensiuni: 186 x 261 x 33 mm
Greutate: 1.11 kg
Editura: Nova Science Publishers Inc

Cuprins

Expressed Sequence Tags in cancer genomics; Protein bioinformatics for drug discovery concavity druggability and antibody druggability; A linkage disequilibrium based statistical approach to discovering interactions among SNP alleles at multiple loci contributing to human skin pigmentation variation; Sufficient conditions for exact penalty in constrained optimization on complete metric spaces; How to create a computational medicine study?; Identifying related cancer types; Sample size Calculation and Power in Genomics Studies; Coupling computational and experimental analysis for the prediction of transcription factor E2F regulatory elements in the human gene promoter; Fast Modeling of Protein Structures Through Multi-level Contact Maps; Differentiating superficial and advances urothelial bladder carcinomas based on gene expression profiles analyzed using Self- Organizing maps; Recent issues and computational approaches for developing prognostic gene signatures from gene expression data; Comparison of values and folding time predictions by using Monte-Carlo and Dynamic Programming approaches; Computational methods for protein structural class prediction; Fundamentals of natural computation in living systems; Extraction of position-sensitive promoter constituents; Mathematical models and bioinformatics approaches; Scripting of molecular structure viewer for data analysis using Lua Language interpreter; Computational medicine research in hematology:a study on hemoglobin and prothrombin disorders.