中草藥生物資訊與程式設計謝長奇~cchsieh/cchsieh@mail.cmu.edu.tw04-23590121#37125授課資料教學目標教導學生于生物資訊學,並指導學生搜尋生物資訊、利用生物資訊相關軟體與建構之生物資訊程式與計算平台。授課方式電腦教室上機實習及課堂教學教學大樓5F視聽電腦教室授課資料評分標準出席狀況:10%、上課態度:20%、學習成果(隨堂考、期中考、期末考):70%參考書目IntroductiontoBioinformatics.StephenA.KrawetzandDavidD.Womble2003.HumanaPress基礎生物資訊實務李炎編著2002藝軒出版社生物資訊入門陳進和等編譯2003藝軒出版社BeginningPerlforBioinformatics.JamesD.Tisdall.2001.O'ReillyPressMasteringPerlforBioinformatics.JamesD.Tisdall.2003.O'ReillyPress生物資訊學電腦技術林仲彥、李士傑、陳淑華、OSB-TW2002歐萊禮基礎生物資訊實務(附光碟)(第二版)本書主要以分子生物學的觀念,介紹如何利用網路上免費的生物資訊工具。如何將片段DNA查出它的可能蛋白質為何?此蛋白質的可能3D結構為何?或是它是否含有“表現段-exon”或“插入段intron”?有否含tRNA、mRNA或rRNA片段?幾個片段的胺基酸排序之間有否演化上的關連性?並繪出演化樹。課程內容次數教學內容1Introduction2NCBIandOtherbiomedicalwebsite3NucleicAcidSequenceAnalysisandInformation4BLASTandSequencealignment5PhylogenicAnalysis6TheEvolutionfromSequenceInformation7GenomeInformationResources8StatisticalAnalysis9Med-Exam課程內容次數教學內容10Perlprogrammingintroduction11Perlprogramminginbioscience12Perlprogramminginsequencesearch13Perlprogramminginsequenceanalysis14Perlprogramminginrestrictionmapandvirtualgel15PerlprogramminginGenbank16PerlprogramminginBLAST17PerlprogramminginClastalW18Finalexam課程關連圖中草藥資源中草藥生物資訊生物化學分析化學藥理學分子生物學生物技術體學(組學)藥理、毒理模型預測中草藥系統演化藥材資源鑑定新資源、新產品開發多元市場經營推廣課程學習路徑圖DatabaseDNAproteinRNAAnalysistoolsSequenceEvolutionPhylogenicBioinformationKnowledgePublicdomainInhousedesignBioinformaticsintroduction生物資訊學利用應用數學、資訊學、統計學和電腦科學的方法研究生物學的問題。目前的生物資訊學基本上只是分子生物學與資訊技術(尤其是網際網路技術)的結合體。生物資訊學的研究材料和結果就是各種各樣的生物學數據,其研究工具是電腦,研究方法包括對生物學數據的搜索(收集和篩選)、處理(編輯、整理、管理和顯示)及利用(計算、模擬)。目前主要的研究方向有:序列比對,基因識別,基因重組,蛋白質結構預測,基因表達,蛋白質反應的預測,以及建立進化論的模型。生物資訊學生物學技術往往生成大量的嘈雜數據。與數據挖掘類似,生物資訊學利用數學工具從大量數據中提取有用的生物學資訊。生物資訊學所要處理的典型問題包括:重新組裝在散彈法DNA測序過程中被打散的DNA序列,從蛋白質的胺基酸序列預測蛋白質結構,利用mRNA微陣列或質譜儀的數據檢驗基因調控的假說。Whatisbioinformatics?Thetermwasfirstcoinedin1988byDr.HwaA.Lim(HAL),andiscommonlyknownasthe“FatherofBioinformatics”.Theoriginaldefinitionwas:“acollectivetermfordatacompilation,organisation,analysisanddissemination”WhatisbioinformaticsTheuseofcomputersinsolvinginformationproblemsinthelifesciences,mainly,itinvolvesthecreationofextensiveelectronicdatabasesongenomes,proteinsequences,etc.Itinvolvestechniquessuchasthethree-dimensionalmodelingofbiomoleculesandbiologicsystems.Whystudybioinformaticsvarietysourcesofdatamakethedataeasilyanduniversallyinterpretablebyscientistspost-genomiceraProgressinghistoryMendelprovedhislawsofhereditarywithvarietiesofpeasandflowersin1865Thefirstproteintobesequenced–insulinThefirstcompletesequencingofanenzyme,ribonucleasein1960Tothesequencingofthefirstcompletegenome(Haemophilusinfluenzae)publishedin1995movedontotechnologiespermittingthesequencing,recombinationandcloningofDNATheHumanGenomeProjectIn1990theunveilingoftheHumanGenomeProject(HGP)bytheUnitedStatesDepartmentofEnergy(DoE)andtheNationalInstitutesofHealthGoals:toidentifyallchemicalbasepairsandallgenesthatmakeupthe23chromosomepairsfoundinhumanDNA“Todevelopthenextgenerationofmethodsforsimulatingcellularbehaviourandpathways”TheHumanGenomeProjectCollaborationof20groupsacrosstheworldTheresultswouldbefreeanddatareleasewouldberapidToidentifyeverybasepairinthegenome-thereare3x109ToassigngenesandwhattheycodeforornotPotentiallyrevolutionisebiomedicalresearchTheHumanGenomeProjectTheinitialestimateswerethatthehumangenomecomprisedsome100,000+genes-nowweknowthereareonly30-40,000onlytwiceasmanyasfoundinawormoraflyGeneOpenReadingFramesThecomplexsplicingtechniquesofhigherorganismsmeanseachprotein-codinggenegeneratesbetween3and6proteins=50,000to500,000proteinsperindividualGeneTheideathat1gene=1proteinisclearlywrongThegenestructureandthecomponentsthatregulateitsexpressionmustbemuchmorecomplexthanpreviouslythoughtStillhaveroughly100,000genesofmicrobes,plantsandanimalswhosefunctionsarestilltoberevealedSystemicbiologyHuman~40,000genes~100,000-150,000splicevariants~500,000-2,000,000proteins(polypeptides)~600-1000metabolicpathwaysSystemicbiologyMolecularinteractioncomplexityMolecularInteractionMapsEvolutionarycomplexityeliminationseries‘omics’revolutionGenomics–thesequencingandannotationofgenomesFunctionalandstructuralgenomics–thecomparisonandcharacterisationofgenomesofdifferentspeciesProteomics–thedescriptionofthecompletesetofproteinsaparticulargenomecodesModelorganismsCheapPlentifulShortgenerationtimesEasilymanipulatedTestnoveldrugcandidatesIllustratingwhichgenes,andthereforewhichproteins,areresponsibleforwhichphenotype/disease85%geneticsimilaritybetweenthemouseandhumangenomeComputersciencecomeintoTheHGPhasbroughttolightthelimitationsoftraditionallabworkBioin