Bioinformatics Algorithms: Design and Implementation in Python

395 Pages·2018·6.7 MB·English

by  Miguel Rocha

Bioinformatics Algorithms

Bioinformatics Algorithms
Design and Implementation in Python
Miguel Rocha
University of Minho, Braga, Portugal
Pedro G. Ferreira
Ipatimup/i3S, Porto, Portugal
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CHAPTER 1
Introduction
1.1 Prelude
Inthelastdecades,importantadvanceshavebeenachievedinthebiologicalandbiomedical
fields,whichhavebeenboostedbyimportantadvancesinexperimentaltechnologies.The
mostknown,andarguablymostrelevant,examplecomesfromtheimpressiveevolutionof
sequencingtechnologiesinthelast40years,boostedbythelargeinvestmentintheHuman
GenomeProjectmainlyinthe1990’s[92,150].
Additionally,otherhigh-throughputtechnologiesformeasuringgeneexpression,proteinor
compoundconcentrationsincells,haveledtoarealrevolutioninbiologicalandmedicalre-
search.Allthesetechniquesarecurrentlyabletogeneratemassiveamountsofthesocalled
omicsdata,thatcanbeusedtofosterscientificresearchinthelifesciencesandpromotethe
developmentofnoveltechnologiesinhealthcare,biotechnologyandrelatedareas.
Merelyastwoexamplesoftheimpactofthesenoveltechnologiesandproduceddata,wecan
pinpointtheimpressivedevelopmentinareassuchaspersonalized(orprecision)medicine
andmetabolicengineeringeffortswithinindustrialbiotechnology.
Precisionmedicineaddressesthegrowingtrendoftailoringtreatmentstothecharacteris-
ticsofindividual(orgroupsof)patients.Thishasbeenmadeincreasinglypossiblebythe
availabilityofgenomic,epigenomic,geneexpression,andothertypesofdataaboutspe-
cificpatients,allowingtodeterminedistinctriskprofilesforcertaindiseases,ortostudy
differentiatedeffectsoftreatmentscorrelatedtopatternsingenomic,epigenomicorgene
expressiondata.Thesedataallowtodesignspecificcoursesofactionbasedonthepatient’s
profiles,allowingmoreaccuratediagnosisandspecifictreatmentplans.Thisfieldisex-
pectedtogrowsignificantlyinthecomingyears,asitisconfirmedbyprojectssuchasthe
100,000GenomesProjectlaunchedbytheUKPrimeMinisterDavidCameronin2012
(https://www.genomicsengland.co.uk/the-100000-genomes-project/)orthe
launchofthePrecisionMedicineInitiative,announcedinJanuary2015byPresidentBarack
Obama,andwhichhasstartedinFebruary2016.
Cancerresearchisanareathatlargelybenefitedfromtherecentadvancesinmolecularassays.
ProjectssuchastheGenomicDataCommons(https://gdc.cancer.gov)ortheInterna-
tionalCancerGenomeConsortium(ICGC,http://icgc.org/)aregeneratingcomprehen-
siveandmulti-dimensionalmapsofthegenomicalterationsincancercellsfromhundredsof
individualsindozensoftumortypeswithavisiblescientific,clinical,andsocietalimpact.
BioinformaticsAlgorithms.DOI:10.1016/B978-0-12-812520-5.00001-8
Copyright©2018ElsevierInc.Allrightsreserved. 1
2 Chapter1
Othercurrentlarge-scaleeffortsboostedbytheuseofhigh-throughputtechnologiesand
ledbyinternationalconsortiaaregeneratingdataatanunprecedentedscaleandchanging
ourviewofhumanmolecularbiology.Ofnoticeareprojectssuchasthe1000Genomes
Project(www.internationalgenome.org/)thatprovidesacatalogofhumangenetic
variationacrossworldwidepopulations;theEncyclopediaofDNAElements(ENCODE,
https://www.encodeproject.org/)hasbuiltamapoffunctionalelementsinthehuman
genome;theEpigenomicsRoadmap(http://www.roadmapepigenomics.org/)ischar-
acterizingtheepigenomiclandscapesofprimaryhumantissuesandcellsortheGenotype-
TissueExpressionproject(GTEx,https://www.gtexportal.org/)whichisproviding
geneexpressionandquantitativetraitlocifrommorethan50humantissues.
Ontheotherhand,metabolicengineeringisrelatedtotheimprovementofspecificmicrobes
usedinindustrialbiotechnologicalprocessestoproduceimportantcompoundsasbio-fuels,
plastics,pharmaceuticals,foods,foodingredientsandotheradded-valuecompounds.Strate-
giesusedtoimprovehostmicrobesincludeblockingcompetingpathwaysthroughgenedele-
tionorinactivation,overexpressingrelevantgenes,introducingheterologousgenesorenzyme
engineering.
Inbothcases,theimpactofdataavailabilityhasbeentremendous,openingnewavenuesfor
scientificadvanceandtechnologicaldevelopment.However,thishasalsoraisedsignificant
challengesinthemanagementandanalysisofsuchcomplexandlargevolumesofdata.Bio-
logicalresearchhasbecomeinmanyaspectsverydata-orientedandthishasbeenintricately
connectedtotheabilitytohandlethesehugeamountsofdatageneratingnovelknowledge,or
asFlorianMarkowetzrecentlyputsit“Allbiologyiscomputationalbiology”[108].There-
fore,thevalueofthesophisticatedcomputationaltoolsthathavebeendevelopedtoaddress
thesedataprocessingandanalysishasbeenundeniable.
ThisbookisaboutBioinformatics,thefieldthataimstohandlethesebiologicaldata,using
computers,andseekingtounravelnovelknowledgefromrawdata.Inthenextsection,we
willdiscussfurtherwhatBioinformaticsis,andthedifferenttasksandscientificdisciplines
thatareinvolvedinthefield.Toclosethechapter,wewilloverviewthecontentoftheremain-
ingofthebooktohelpthereaderinthetaskofbetternavigatingit.
1.2 What is Bioinformatics
Bioinformaticsisamulti-disciplinaryfieldattheintersectionofBiology,ComputerScience,
andStatistics.Naturally,itsdevelopmenthasfollowedthetechnologicaladvancesandre-
searchtrendsinBiologyandInformationTechnologies.Thus,althoughitisstillayoungfield,
itisevolvingfastanditsscopehasbeensuccessivelyredefined.Forinstance,theNationalIn-
stituteofHealth(NIH)definesBioinformaticsinabroadway,asthe“research,development,
Introduction 3
orapplicationofcomputationaltoolsandapproachesforexpandingtheuseofbiological,
medical,biological,behavioral,orhealthdata”[79].Accordingtothisdefinition,thetasks
involvedincludedataacquisition,storage,archival,analysis,andvisualization.
Someauthorshaveamorefocuseddefinition,whichrelatesBioinformaticsmainlytothe
studyofmacromoleculesatthecellularlevel,andemphasizeitscapabilityofhandlinglarge-
scaledata[105].Indeed,sinceitsappearance,themaintasksofBioinformaticshavebeen
relatedtohandlingdataatacellularlevel,andthiswillalsobethefocusofthisbook.
StillinthepreviousseminaldocumentfromtheNIH,therelatedfieldofComputationalBiol-
ogyisdefinedasthe“developmentandapplicationofdata-analyticalandtheoreticalmethods,
mathematicalmodeling,andcomputationalsimulationtechniquestothestudyofbiolog-
ical,behavioral,andsocialsystems”.Thus,althoughdeeplyrelated,andsometimesused
interchangeablybysomeauthors,thefirst(Bioinformatics)relatestoamoretechnologically
orientedview,whilethesecondismorerelatedtothestudyofnaturalsystemsandtheirmod-
eling.Thisdoesnotpreventalargeoverlapofthetwofields.
Bioinformaticstacklesalargenumberofresearchproblems.Forinstance,theBioinformatics
(https://academic.oup.com/bioinformatics)journalpublishesresearchonapplica-
tionareasthatincludegenomeanalysis,phylogenetics,genetic,andpopulationanalysis,gene
expression,structuralbiology,textmining,imageanalysis,andontologiesanddatabases.
TheNationalCenterforBiotechnologyInformation(NCBI,https://www.ncbi.nlm.nih.
gov/Class/MLACourse/Modules/MolBioReview/bioinformatics.html)unfolds
Bioinformaticsintothreemainareas:
• developingnewalgorithmsandstatisticstoassessrelationshipswithinlargedatasets;
• analyzingandinterpretingdifferenttypesofdata(e.g.nucleotideandaminoacidse-
quences,proteindomains,andproteinstructures);
• developingandimplementingtoolsthatenableefficientaccessandmanagementofdiffer-
enttypesofinformation.
Thisbookwillfocusmainlyonthefirstoftheseareas,coveringthemainalgorithmsthathave
beenproposedtoaddressBioinformaticstasks.Theemphasiswillbeputonalgorithmsfor
sequenceprocessingandanalysis,consideringbothnucleotideandaminoacidsequences.
1.3 Book’s Organization
Thisbookisorganizedintofourlogicalpartsencompassingthemajorthemesaddressedin
thistext,eachcontainingchaptersdealingwithspecifictopics.
4 Chapter1
Inthefirstpart,wherethischapterisincluded,weintroducethefieldofBioinformatics,pro-
vidingrelevantconceptsanddefinitions.Sincethisisaninterdisciplinaryfield,wewillneed
toaddresssomefundamentalaspectsregardingalgorithmsandthePythonprogramminglan-
guage(Chapter2),coversomebiologicalbackgroundneededtounderstandthealgorithmsput
forwardinthefollowingpartsofthebook(Chapter3).
Thesecondpartofthisbookaddressesanumberofproblemsrelatedtosequenceanalysis,in-
troducingalgorithmsandproposingillustrativePythonfunctionsandprogramstosolvethem.
TheBioinformaticstasksaddressedwillcovertopicsrelatedwithbasicsequenceprocess-
ingandanalysistasks,suchastheonesinvolvedintranscriptionandtranslation(Chapter4),
algorithmsforfindingpatternsinsequences(Chapter5),pairwiseandmultiplesequence
alignmentalgorithms(Chapters6and8),searchinghomologoussequencesindatabases
(Chapter7),algorithmsforphylogeneticanalysisfromsequences(Chapter9),biological
motifdiscoverywithdeterministicandstochasticalgorithms(Chapters10,11),andfinally
HiddenMarkovModelsandtheirapplicationsinBioinformatics(Chapter12).
Thethirdpartofthebookwillfocusonmoreadvancedalgorithms,basedingraphsasdata
structures,whichwillallowtohandlelarge-scalesequenceanalysistasks,suchastheones
typicallyinvolvedinprocessingandanalyzingnext-generationsequencing(NGS)data.This
partstartswithanintroductiontographdatastructuresandalgorithms(Chapter13),addresses
theconstructionandexplorationofbiologicalnetworksusinggraphs(Chapter14),focuseson
algorithmstohandleNGSdata,addressingthetasksofassemblingreadsintofullgenomes(in
Chapter15)andmatchingreadstoreferencegenomes(inChapter16).
ThebookcloseswithPartIV,whereanumberofcomplementaryresourcestothisbookare
identified(Chapter17),includinginterestingbooksandarticles,onlinecourses,andPython
relatedresources,andsomefinalwordsareputforward.
Asacomplementarysourceofinformation,awebsitehasbeendevelopedtocomplementthe
book’smaterials,includingcodeexamplesandproposedsolutionsformanyoftheexercises
putforwardintheendofeachchapter.