Managing Your Biological Data With Python - Via Allegra; Rother Kristian; Tramontano Anna | Libro Chapman And Hall/Crc 04/2014 - HOEPLI.it


home libri books ebook dvd e film top ten sconti 0 Carrello


Torna Indietro

via allegra; rother kristian; tramontano anna - managing your biological data with python

Managing Your Biological Data with Python

; ;




Disponibilità: Normalmente disponibile in 20 giorni
A causa di problematiche nell'approvvigionamento legate alla Brexit sono possibili ritardi nelle consegne.


PREZZO
72,98 €
NICEPRICE
69,33 €
SCONTO
5%



Questo prodotto usufruisce delle SPEDIZIONI GRATIS
selezionando l'opzione Corriere Veloce in fase di ordine.


Pagabile anche con 18App Bonus Cultura e Carta del Docente


Facebook Twitter Aggiungi commento


Spese Gratis

Dettagli

Genere:Libro
Lingua: Inglese
Pubblicazione: 04/2014
Edizione: 1° edizione





Note Editore

Take Control of Your Data and Use Python with Confidence Requiring no prior programming experience, Managing Your Biological Data with Python empowers biologists and other life scientists to work with biological data on their own using the Python language. The book teaches them not only how to program but also how to manage their data. It shows how to read data from files in different formats, analyze and manipulate the data, and write the results to a file or computer screen. The first part of the text introduces the Python language and teaches readers how to write their first programs. The second part presents the basic elements of the language, enabling readers to write small programs independently. The third part explains how to create bigger programs using techniques to write well-organized, efficient, and error-free code. The fourth part on data visualization shows how to plot data and draw a figure for an article or slide presentation. The fifth part covers the Biopython programming library for reading and writing several biological file formats, querying the NCBI online databases, and retrieving biological records from the web. The last part provides a cookbook of 20 specific programming "recipes," ranging from secondary structure prediction and multiple sequence alignment analyses to superimposing protein three-dimensional structures. Tailoring the programming topics to the everyday needs of biologists, the book helps them easily analyze data and ultimately make better discoveries. Every piece of code in the text is aimed at solving real biological problems.




Sommario

Getting StartedThe Python Shell In This Chapter You Will Learn Story: Calculating the ?G of ATP Hydrolysis What Do the Commands Mean? Examples Testing Yourself Your First Python Program In This Chapter You Will Learn Story: How to Calculate the Frequency of Amino Acids from InsulinWhat Do the Commands Mean? Examples Testing Yourself Data ManagementAnalyzing a Data Column In This Chapter You Will Learn Story: Dendritic Lengths What Do the Commands Mean? Examples Testing Yourself Parsing Data Records In This Chapter You Will Learn Story: Integrating Mass Spectrometry Data into Metabolic PathwaysWhat Do the Commands Mean? Examples Testing Yourself Searching DataIn This Chapter You Will Learn Story: Translating an RNA Sequence into the Corresponding Protein SequenceWhat Do the Commands Mean? Examples Testing Yourself Filtering DataIn This Chapter You Will Learn Story: Working with RNA-Seq Output DataWhat Do the Commands Mean? Examples Testing Yourself Managing Tabular DataIn This Chapter You Will Learn Story: Determining Protein ConcentrationsWhat Do the Commands Mean? Examples Testing Yourself Sorting DataIn This Chapter You Will Learn Story: Sort a Data TableWhat Do the Commands Mean? Examples Testing Yourself Pattern Matching and Text MiningIn This Chapter You Will Learn Story: Search a Phosphorylation Motif in a Protein SequenceWhat Do the Commands Mean? Examples Testing Yourself Modular ProgrammingDivide a Program into FunctionsIn This Chapter You Will Learn Story: Working with Three-Dimensional Coordinate FilesWhat Do the Commands Mean? Examples Testing Yourself Managing Complexity with ClassesIn This Chapter You Will Learn Story: Mendelian InheritanceWhat Do the Commands Mean? Examples Testing Yourself DebuggingIn This Chapter You Will Learn Story: When Your Program Does Not WorkWhat Do the Commands Mean? Examples Testing Yourself Using External Modules: The Python Interface to RIn This Chapter You Will Learn Story: Reading Numbers from a File and Calculating Their Mean Value Using R with PythonWhat Do the Commands Mean? Examples Testing Yourself Building Program PipelinesIn This Chapter You Will Learn Story: Building an NGS PipelineWhat Do the Commands Mean? Examples Testing Yourself Writing Good ProgramsIn This Chapter You Will Learn Problem Description: UncertaintyWhat Do the Commands Mean? Examples Testing Yourself Data VisualizationCreating Scientific DiagramsIn This Chapter You Will Learn Story: Nucleotide Frequencies in the RibosomeWhat Do the Commands Mean? Examples Testing Yourself Creating Molecule Images with PyMOLIn This Chapter You Will Learn Story: The Zinc FingerSeven Steps to Create a High-Resolution ImageExamples Testing Yourself Manipulating ImagesIn This Chapter You Will Learn Story: Plot a PlasmidWhat Do the Commands Mean? Examples Testing Yourself BiopythonWorking with Sequence DataIn This Chapter You Will Learn Story: How to Translate a DNA Coding Sequence into the Corresponding Protein Sequence and Write It to a FASTA FileWhat Do the Commands Mean? Examples Testing Yourself Retrieving Data from Web ResourcesIn This Chapter You Will Learn Story: Searching Publications by Keywords in PubMed, Downloading the Corresponding Records, and Writing Papers Published in a Given Year to a FileWhat Do the Commands Mean? Examples Testing Yourself Working with 3D Structure DataIn This Chapter You Will Learn Story: Extracting Atom Names and Three-Dimensional Coordinates from a PDB FileWhat Do the Commands Mean? Examples Testing Yourself CookbookRecipe 1: The PyCogent Library Recipe 2: Reversing and Randomizing a SequenceRecipe 3: Creating a Random Sequence with Probabilities Recipe 4: Parsing Multiple Sequence Alignments Using Biopython Recipe 5: Calculating a Consensus Sequence from a Multiple Sequence Alignment Recipe 6: Calculating the Distance between Phylogenetic Tree Nodes Recipe 7: Codon Frequencies in a Nucleotide Sequence Recipe 8: Parsing RNA 2D Structures in the Vienna FormatRecipe 9: Parsing BLAST XML OutputRecipe 10: Parsing SBML Files Recipe 11: Running BLAST Recipe 12: Accessing, Downloading, and Reading Web Pages in Python Recipe 13: Parsing HTML Files Recipe 14: Split a PDB File into PDB Chain Files Recipe 15: Find the Two Closest Ca Atoms in a PDB Structure Recipe 16: Extract the Interface between Two PDB ChainsRecipe 17: Building Homology Models Using Modeller Recipe 18: RNA 3D Homology Modeling with ModeRNA Recipe 19: Calculating RNA Base Pairs from a 3D Structure Recipe 20: A Real Case of Structural Superimposition: The Serine Protease Catalytic Triad Appendix A: Command OverviewAppendix B: Python ResourcesAppendix C: Record SamplesAppendix D: Handling Directories and Programs with UNIX







Altre Informazioni

ISBN:

9781439880937

Condizione: Nuovo
Collana: Chapman & Hall/CRC Mathematical and Computational Biology
Dimensioni: 9.25 x 6.125 in Ø 1.80 lb
Formato: Brossura
Illustration Notes:33 b/w images and 8 tables
Pagine Arabe: 560






Utilizziamo i cookie di profilazione, anche di terze parti, per migliorare la navigazione, per fornire servizi e proporti pubblicità in linea con le tue preferenze. Se vuoi saperne di più o negare il consenso a tutti o ad alcuni cookie clicca qui. Chiudendo questo banner o proseguendo nella navigazione acconsenti all’uso dei cookie.

X