Similar compounds searching system by using the gene expression microarray database.docx

Similar compounds searching system by using the gene expression microarray database.docx

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Similarcompoundssearchingsystembyusingthegeneexpressionmicroarraydatabase

425articlesfoundfor:

pub-date>2003andtak（（（ChemicalDatabase）or（ComputerChemistry）or（databaseChemistry））and（（SoftwareDevelopment）or（Largedatabase）or（ApplicationDevelopment）or（visualstudio）orC++orDerivativesor（integrationofmulti-databasesystem）））

计算机化学

计算机软件开发

VS.net或C＋＋

大型数据库

化学专业数据库的开发

应用软件开发

化学数据库

多数据库系统的整合

应用衍生

ComputerChemistry

ComputerSoftwareDevelopment

VS.netorC++

Largedatabase

DevelopmentofthedatabaseChemistry

ApplicationDevelopment

ChemicalDatabase

Theintegrationofmulti-databasesystem

ApplicationofDerivatives

GaussDal:

Anopensourcedatabasemanagementsystemforquantumchemicalcomputations 

ComputerPhysicsCommunications

AnopensourcesoftwaresystemcalledGaussDalformanagementofresultsfromquantumchemicalcomputationsispresented.Chemicaldatacontainedinoutputfilesfromdifferentquantumchemicalprogramsareautomaticallyextractedandincorporatedintoarelationaldatabase（PostgreSQL）.TheStructuralQueryLanguage（SQL）isusedtoextractcombinationsofchemicalproperties（e.g.,molecules,orbitals,thermo-chemicalproperties,basissetsetc.）intodatatablesforfurtherdataanalysis,processingandvisualization.Thistypeofdatamanagementisparticularlysuitedforprojectsinvolvingalargenumberofmolecules.InthecurrentversionofGaussDal,parsersforGaussianandDaltonoutputfilesaresupported,howeverfutureversionsmayalsoincludeparsersforotherquantumchemicalprograms.

ForvisualizationandanalysisofgenerateddatatablesfromGaussDalwehaveusedthelocallydevelopedopensourcesoftwareSciCraft.

Programsummary

Titleofprogram:

GaussDal

Catalogueidentifier:

ADVT

ProgramsummaryURL:

http:

//cpc.cs.qub.ac.uk/summaries/ADVThttp:

//cpc.cs.qub.ac.uk/summaries/ADVT

Programobtainablefrom:

CPCProgramLibrary,Queen'sUniversityofBelfast,N.Ireland

Computers:

Any

Operatingsystemunderwhichthesystemhasbeentested:

Linux

Programminglanguageused:

Python

Memoryrequiredtoexecutewithtypicaldata:

256MB

No.ofbitsinword:

32or64

No.ofprocessorsused:

1

Hasthecodebeenvectorizedorparallelized?

:

No

No.oflinesindistributedprogram,includingtestdata,etc:

543 531

No.ofbytesindistributionprogram,includingtestdata,etc:

7 718 121

Distributionformat:

tar.gzipfile

Natureofphysicalproblem:

Handlingoflargeamountsofdatafromquantumchemistrycomputations.

Methodofsolution:

UseofSQLbaseddatabaseandquantumchemistrysoftwarespecificparsers.

Restrictiononthecomplexityoftheproblem:

ProgramiscurrentlylimitedtoGaussianandDaltonoutput,butexpandabletootherformats.Generatessubsetsofmultipledatatablesfromoutputfiles.

ArticleOutline

1.Introduction

2.Softwarerequirements

2.1.Relatedsoftware

3.Designandconstruction

3.1.OverallstructureofGaussDal

3.2.Databasestructure

3.3.Technologydecisions

3.4.Visualizationanddataanalysis

3.5.TheSciCraftsystem

3.5.1.Integration

3.5.2.Visualprogramming

3.5.3.TheGaussDalnode

4.TheSQLlanguage

4.1.Relations

4.2.Structuredqueries

4.2.1.SomebasicSQLcommands

5.GaussDalwebsolution

5.1.Webinterface

5.1.1.Submittingcomputations

5.2.PhpPgAdmin

6.Applicationexamples

6.1.Forcefieldparametrization

6.1.1.Descriptionofdataset

6.1.2.QCcalculations

6.1.3.TheSQLquery

6.1.4.DataanalysiswithSciCraft

6.2.Electrophilicadditiontopropene

6.2.1.Descriptionofdataset

6.2.2.QCcalculations

6.2.3.TheSQLquery

6.2.4.DataanalysiswithSciCraft

7.Discussion

8.Outputextract

References

Structurealertsforcarcinogenicity,andtheSalmonellaassaysystem:

Anovelinsightthroughthechemicalrelationaldatabasestechnology  

MutationResearch/ReviewsinMutationResearch

Inthepastdecades,chemicalcarcinogenicityhasbeentheobjectofmechanisticstudiesthathavebeentranslatedintovaluableexperimental（e.g.,theSalmonellaassayssystem）andtheoretical（e.g.,compilationsofstructurealertsforchemicalcarcinogenicity）models.Thesefindingsremainthebasisofthescienceandregulationofmutagensandcarcinogens.Recentadvancesintheorganizationandtreatmentoflargedatabasesconsistingofbothbiologicalandchemicalinformationnowadaysallowsforamucheasierandmorerefinedviewofdata.Thispaperreviewsrecentanalysesonthepredictiveperformanceofvariouslistsofstructurealerts,includinganewcompilationofalertsthatcombinespreviousworkinanoptimizedformforcomputerimplementation.TherevisedcompilationispartoftheToxtree1.50software（freelyavailablefromtheEuropeanChemicalsBureauwebsite）.TheuseofstructuralalertsforthechemicalbiologicalprofilingofalargedatabaseofSalmonellamutagenicityresultsisalsoreported.

Togetherwithbeingarepositoryofthescienceonthechemicalbiologicalinteractionsatthebasisofchemicalcarcinogenicity,theSAshaveacrucialroleinpracticalapplicationsforriskassessment,for:

（a）descriptionofsetsofchemicals;（b）preliminaryhazardcharacterization;（c）formationofcategoriesfore.g.,regulatorypurposes;（d）generationofsubsetsofcongenericchemicalstobeanalyzedsubsequentlywithQSARmethods;（e）prioritysetting.

AnimportantaspectofSAsaspredictivetoxicitytoolsisthattheyderivedirectlyfrommechanisticknowledge.Thecrucialroleofmechanisticknowledgeintheprocessofapplying（Q）SARconsiderationstoriskassessmentshouldbestronglyemphasized.Mechanisticknowledgeprovidesagroundforinteractionanddialoguebetweenmodeldevelopers,toxicologistsandregulators,andpermitstheintegrationofthe（Q）SARresultsintoawiderregulatoryframework,wheredifferenttypesofevidenceanddataconcurorcomplementeachotherasabasisformakingdecisionsandtakingactions.

ArticleOutline

1.Introduction

2.Background

2.1.Themechanisticresearch

2.2.Newdevelopmentsintheorganizationandexploitationofchemicalbiologicaldata

3.Structurealertsandtheirevaluation

4.SAspredictivityandthechangingpatternofchemicalsinuse

5.SAsforcarcinogenicity:

newdevelopments

5.1.TheperformanceofthenewlistofSAs

6.ChemicalbiologicalprofilingofaSalmonellamutagenicitydatabase

7.Finalconsiderations

Conflictofinterest

References

Adecisionsupportgridforintegratedmolecularsolventdesignandchemicalprocessselection 

Computers&ChemicalEngineering

Theprocessengineeringdomainmakesaninterestingapplicationareaforgridtechnologiesasproblemsolvinggenerallyinvolvesmultiplesoftwareanddataresourcesandheavycomputations.Therearenumerouscomputationallydemandingapplicationsthatcanbenefitfromgridcomputingsuchasmolecularsimulationsandlarge-scaleoptimizations.Wereportonaprototypegridforintegratedprocessandmoleculardesigntodemonstratethepotentialofgridsintheprocess-engineeringarena.Theprototypeintegratesin-housesolventandprocessdesigntoolswithexternaldistributedcomputationandstorageresourcesaswellasweb-databasesandcomputernetworks.Amiddlewarearchitectureisproposedintheformofaproblem-solvingenvironmentasameansofinterfacingtheheterogeneousgridcomponents.Thegridoperationsandfunctionalitiesareexposedtotheuserthroughaprototypeweb-portalthatenablestheseamlessaccessandutilizationoftheavailableresources.Thedevelopedprototypeisillustratedwithanapplicationcase.

ArticleOutline

1.Introduction

2.Generalconceptsofgridcomputing

3.GridcomputingrelateddevelopmentsinCAPE

3.1.InteroperabilitythroughtheCAPE-OPENstandard

3.2.Agent-basedandservice-orientedapproaches

3.3.Designandoptimizationonthegrid

4.Integratedsolventandprocesssynthesis:

agridcomputingparadigm

4.1.Theintegratedsolventandprocesssynthesisproblem—overview

4.2.Incentivesforgridcomputinginintegratedsolventandprocesssynthesis

5.Thegridcomputingprototypeforintegratedsolventandprocessdesign

5.1.Outlineofprototype

5.2.Availableinfrastructure

5.3.Problem-solvingenvironment—Web/Gridserviceslayer

5.3.1.Workflowgenerator

5.3.2.Queryservices

5.3.3.Deploymentservices

5.3.4.Resourceallocatoranddatamanager:

staticoperation

5.3.5.Jobscheduler

5.4.Workflowandparalleloptimizationstrategies

5.4.1.Workflowstrategiestargetedbytheproposedarchitecture

5.4.2.Targetedparalleloptimizationstrategiesandfuturedirections

5.5.Web-portal

6.Illustrativeexample

6.1.Designproblem

6.2.Targetedsolutionfeaturesanddiscussionofresults

6.2.1.Stochasticoptimalityexperiments

6.2.2.Queryofmoleculesandstorage

7.Concludingremarksandfuturedevelopments

References

Overviewoftheapplicationsofthermodynamicdatabasestosteelmakingprocesses 

Calphad

Computerizedthermodynamicdatabasesforsolidandliquidsteel,slagsandsolidoxidesolutions,forlargenumbersofcomponents,havebeendevelopedoverthelastthreedecadesbycriticalevaluation/optimizationofallavailablephaseequilibriumandthermodynamicdata.Thedatabasescontainmodelparametersspecificallydevelopedformoltenslags,liquidandsolidsteelandsolidoxidesolutions.Withuser-friendlysoftware,whichaccessesthesedatabases,complexchemicalreactionsandphaseequilibriaoccurringthroughoutthesteelmakingprocesscanbecalculatedoverwiderangesoftemperature,oxygenpotentialandpressure.Inthepresentarticle,thethermodynamicmodelsanddatabasesformoltenslagandliquidsteelincludedinwell-knownthermochemicalpackagesandtheirapplicationstocomplexsteelmak