book

Bioinformatics Programming Using Python

by Mitchell L Model

December 2009

Intermediate to advanced

521 pages

15h 26m

English

O'Reilly Media, Inc.

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IntroductionAbout This BookAbout BioinformaticsAbout the ReaderPythonSome ContextThe Python LanguageInstalling PythonRunning PythonNotesReading and Reference RecommendationsExample CodeUnfortunate and Unavoidable Vocabulary OverlapCommentsConventions Used in This BookWe’d Like to Hear from YouUsing Code ExamplesSafari® Books OnlineAcknowledgments
Simple ValuesBooleansIntegersFloatsStringsExpressionsNumeric OperatorsLogical OperationsString OperationsString operatorsSubscriptionSlicingCallsFunction callsMethod callsCompound ExpressionsTips, Traps, and TracebacksTipsStatements and expressionsRunning Python interactivelyTrapsTracebacks
Assigning NamesDefining FunctionsFunction ParametersComments and DocumentationAssertionsDefault Parameter ValuesUsing ModulesImportingModule namespacesThe random modulePython FilesTips, Traps, and TracebacksTipsNamesFunction definitionsExecuting codeUsing IDLEManaging Python filesTrapsTracebacks
SetsSequencesStrings, Bytes, and BytearraysCreatingTestingSearchingReplacingChanging caseReformattingThe format method and functionRangesTuplesTuple syntaxTuple packing and unpackingListsStatements that modify listsList modification methodsSequence-oriented string methodsMappingsDictionariesDictionary example: RNA codon translation tableDictionary operationsDictionary methodsStreamsFilesCreating file objectsFile methodsExampleGeneratorsCollection-Related Expression FeaturesComprehensionsList comprehensionsSet and dictionary comprehensionsGenerator expressionsConditional comprehensionsNested comprehensionsFunctional ParametersThe parameter “key”Function objectsAnonymous functionsTips, Traps, and TracebacksTipsLanguage featuresDeveloping and testing codeTrapsTracebacks
ConditionalsLoopsSimple Loop ExamplesInitialization of Loop ValuesLooping ForeverLoops with Guard ConditionsIterationsIteration StatementsKinds of IterationsDoCollectCombineSearchFilterNested iterationsRecursive iterationsException HandlersPython ErrorsTracebacksRuntime errorsException Handling StatementsOptional features of exception handling statementsException handling and generator objectsRaising ExceptionsThe raise statementRaising an exception to end a loopExtended ExamplesExtracting Information from an HTML FileThe Grand Unified Bioinformatics File ParserReading the sequences in a FASTA fileGeneralized parsingParsing GenBank FilesTranslating RNA SequencesStep 1Step 2Step 3Step 4Step 5Constructing a Table from a Text FileStep 1Step 2Step 3Step 4Step 5Tips, Traps, and TracebacksTipsTrapsTracebacks
Defining ClassesInstance AttributesAccess methodsPredicate methodsInitialization methodsString methodsModification methodsAction methodsSupport methodsSummaryClass AttributesClass fieldsClass methodsClasses as objectsClass and Method RelationshipsDecompositionClass decompositionMethod decompositionSingleton classesInheritanceDefining subclassesFactoring out common codeGeneralizationSubclass methodsTips, Traps, and TracebacksTipsTrapsTracebacks
System EnvironmentDates and Times: datetimeClassesInstance creationOperationsMethodsSystem InformationThe Python runtime environment: sysThe system clock: timeCommand-Line UtilitiesReading multiple files: fileinputCommand-line options: optparseCommand-line commands: subprocessCommunicationsSending email: smtplibLogging: loggingThe FilesystemOperating System Interface: osEnvironment accessManaging files and directoriesDirectoriesFilesDirectory contentsTemporary files: tempfileManipulating Paths: os.pathPath componentsPath manipulationsPath informationFilename Expansion: fnmatch and globfnmatchglobShell Utilities: shutilComparing Files and DirectoriesFile and directory comparison: filecmpShowing the differences between two files: difflibWorking with TextFormatting Blocks of Text: textwrapString Utilities: stringComma- and Tab-Separated Formats: csvString-Based Reading and Writing: ioPersistent StoragePersistent Text: dbmPersistent Objects: pickleKeyed Persistent Object Storage: shelveDebugging ToolsThe Python debugger: pdbThe IDLE debuggerTips, Traps, and TracebacksTipsTrapsTracebacks
Fundamental SyntaxFixed-Length MatchingLiteral matchesCharacter setsCharacter classesBoundariesVariable-Length MatchingRepetitionGreedy Versus Nongreedy MatchingGrouping and DisjunctionThe Actions of the re ModuleFunctionsFlagsMethodsResults of re Functions and MethodsMatch Object FieldsMatch Object MethodsPutting It All Together: ExamplesSome Quick ExamplesUsing regular expressions to ignore caseListing files in a directory, excluding someFinding open reading framesExtracting Descriptions from Sequence FilesExtracting Entries From Sequence FilesUsing regular expressions to extract entriesKeeping track of the position between callsBuffering inputTips, Traps, and TracebacksTipsTrapsTracebacks
HTMLSimple HTML ProcessingSearching HTML textMore elaborate HTML pattern matchingTurning HTML into plain textStructured HTML ProcessingProblems with HTML pattern matchingStructured HTML parsing: html.parserXMLThe Nature of XMLAn XML File for a Complete GenomeThe ElementTree ModuleGetting started with ElementTreeNavigating around an ElementTreeEvent-Based ProcessingFunction calls, exceptions, and the call stackCallbacks: Reversed function callsProgramming for an event-based processorexpatObtaining a single piece of informationExtracting a few pieces of dataGetting the content of all tags with a specified nameTips, Traps, and TracebacksTipsTrapsTracebacks

Manipulating URLs: urllib.parseDisassembling URLsAssembling URLsOpening Web Pages: webbrowserModule FunctionsConstructing and Submitting QueriesConstructing and Viewing an HTML PageWeb ClientsMaking the URLs in a Response AbsoluteConstructing an HTML Page of Extracted LinksDownloading a Web Page’s Linked FilesWeb ServersSockets and ServersServer fundamentalsRunning a server: The http.server moduleCGIServing CGI requestsSetting up CGICGI script arguments and responsesSimple Web ApplicationsUsing CGI scriptsHTML forms with CGI scriptsTips, Traps, and TracebacksTipsWeb pagesDebugging CGI scriptsHTTP serversTrapsTracebacks
Representation in Relational DatabasesDatabase TablesAvoiding duplication of valuesRepresentation of relationshipsDatabase definitionA Restriction Enzyme DatabaseThe dataReading the dataA schema for the Rebase databaseUsing Relational DataSQL BasicsUsing the sqlite3 moduleConnecting to the databaseCreating the databaseLoading data into tablesSQL QueriesSimple database queriesQualified database queriesRelationship queriesQuerying the Database from a Web PageHTML framesAn HTML page of query formsTips, Traps, and TracebacksTipsTrapsTracebacks
Introduction to Graphics ProgrammingConceptsCoordinate systemComponentsPropertiesGUI ToolkitsGUI toolkits for PythonUsing a GUI toolkitStructured Graphics with tkintertkinter FundamentalsThe basic stepsCommon widget optionsCanvas drawing methodsWriting the contents of a canvas to a PostScript fileExamplesAn abstract class for tkinter graphicsDot plotsHistogramsStructured Graphics with SVGSVG File ContentsSVG tagsSVG stylesExamplesHistograms of codon useSequencing trace file curves using SVGTips, Traps, and TracebacksTipsTrapsSVG trapsTracebacks
Language ComponentsSpecial Syntactic ElementsKeywordsSpecial NamesOperatorsAnonymous FunctionsTypes and ExpressionsStatementsNotes
Types and General OperationsCommon OperationsCreating CollectionsSpecific Collection TypesSetsSequencesStringsListsMappingsStreamsFile objectsGeneratorsIteration TemplatesBasic Iteration TemplatesFiltering TemplatesOther Kinds of Templates

Overview

Powerful, flexible, and easy to use, Python is an ideal language for building software tools and applications for life science research and development. This unique book shows you how to program with Python, using code examples taken directly from bioinformatics. In a short time, you'll be using sophisticated techniques and Python modules that are particularly effective for bioinformatics programming.

Bioinformatics Programming Using Python is perfect for anyone involved with bioinformatics -- researchers, support staff, students, and software developers interested in writing bioinformatics applications. You'll find it useful whether you already use Python, write code in another language, or have no programming experience at all. It's an excellent self-instruction tool, as well as a handy reference when facing the challenges of real-life programming tasks.

Become familiar with Python's fundamentals, including ways to develop simple applications
Learn how to use Python modules for pattern matching, structured text processing, online data retrieval, and database access
Discover generalized patterns that cover a large proportion of how Python code is used in bioinformatics
Learn how to apply the principles and techniques of object-oriented programming
Benefit from the "tips and traps" section in each chapter