:-['observations/metabolites/10Feb11-KGGEName/ternaryMet_newOndexID.pl']. %%hiroaki_60Met %:-['observations/metabolites/10Feb11-KGGEName/foldInfo.pl']. -- this is unnecessary when doing leave-one-out :-['observations/ge/allDoeseGE.pl']. %Feb17-ThreeState-Prolog-ProbWithoutQuotes/linkFile set(ge_data_available,yes). %:-['regulationRules/enzymeLimiting_substrateLimiting/t_control.pl']. %:-['regulationRules/enzymeLimiting_substrateLimiting_counting/t_control.pl']. %:-['regulationRules/enzymeLimiting_substrateLimiting_counting_EC/t_control.pl']. %:-['regulationRules/2010_9_23/t_SID.pl']. %:-['regulationRules/2010_9_23/t_singleC1.pl']. %:-['regulationRules/2011_01_21/t_noEC_constrainIncoporate.pl']. :-['regulationRules/2011_05_24/t_tomatoComparable.pl']. % t_simpleRecord %t_noEC_constrainIncoporate %:-['regulationRules/2011_01_21/t_noEC_assumptionUpdated.pl']. :-['networkData/2012_2/keggmap_rn_rno.pl']. :-['networkData/ubiquitous_compounds/ondexID_2012_2.pl']. %:-['networkData/2011_1/kegg_rno-PreferredFirstNameFiltered-Mapped-RelationsCollapsed-UbiquitousRemoved.pl']. %:-['networkData/2010_9_1/kegg_rno_removed.pl']. %-- :-['networkData/a.pl']. %:-['networkData/m.pl']. %--:-['networkData/visualizationProcessing.pl']. :-['score/score.pl']. sharedOutputToC:- numbersList(157,208,AllEIs), gen_output_readIn_candiateH(AllEIs), indentifySharedHs(AllEIs,T_EITIs,OrderedGroupedCandidateHs), outputToC(PosEIs,T_EITIs), tell('sharedCandidate.pl'), filterIsolated(OrderedGroupedCandidateHs), told. s:- numbersList(157,208,AllEIs), indentifySharedHs(AllEIs). hs(PosEIs):- %(PosEIs) PosEIs=[75,116], %4,32,37%PosEIsNOR_Late % [89,90,91,92,96,97,98,101,102,103,105,106,107,108,109] prefixTreeBuilder(PosEIs),listing, claNode(startNode,StartNodeCoverage), tell('cancer_hypothesisSelection_day1.txt'), hypothesisSelection(startNode-StartNodeCoverage,FinalHypothesis), print_list(FinalHypothesis),nl, told. hs0:- getAllEx_oneTimePoint('Day1',PosEIs), prefixTreeBuilder(PosEIs), claNode(startNode,StartNodeCoverage), hypothesisSelection(startNode-StartNodeCoverage,FinalHypothesis), FinalHypothesis=[IsolatedEIExplanations,CombinedExplanation], write('Here are the final Hypothesis'),nl, print_list(CombinedExplanation),nl, nl, write('The followings are explanations which do not overlap with others '),nl, print_list(IsolatedEIExplanations),nl, tell('day1_dose1000.txt'), translateFinalHypothesis([IsolatedEIExplanations,CombinedExplanation],FinalH), %write('Finish translating'),nl, write('# Isolated Explanations'), analyzeIsolated(IsolatedEIExplanations), nl,write('# Shared Control Points Explanations'), analyzeCombined(CombinedExplanation), write('#Finish explanation for each metabolite'),nl, told. g0:- numbersList(1,208,PosEIs0), selectlist(zeroHypothesisCheck,PosEIs0,PosEIs), nl,write(PosEIs),nl, ord_subtract(PosEIs0,PosEIs,EmptyH_EIList), write(EmptyH_EIList),nl, findall(EI,ex(EI,concentration(MID,no_change,Time),1),NoChangeList),write(NoChangeList),nl, (EmptyH_EIList==NoChangeList -> write('yes,the same'); write('not the same'), ord_subtract(EmptyH_EIList,NoChangeList,Diff_EIList), nl,write(Diff_EIList) ). zeroHypothesisCheck(EI):- g(EI,T),T\==[]. /*Day1=[[3,4,5,7,9,10,11,16,20,22,26,27,29,30,32,36,37,38,40,41,50,53,56], Day4=[69,70,71,72,73,75,76,77,80,81,82,83,84,86,88,93,95,96,97,98,99,100,101,103,106,109,110,111,112,114,116,118,121,123,124,125], Day7=[136,137,139,140,141,142,143,145,148,151,153,154,158,160,161,162,163,164,165,166,169,172,175,176,178,180,183,188,189,190,191], Day14=[202,203,204,205,207,208,209,211,216,221,222,226,228,230,232,235,238,239,240,242,244,246,248,250,252,255,257] */ c:- statistics(cputime,[Total1,Previous]), tell('cancer_day14.txt'), %numbersList(231,272,PosEIsNOR_Late), %PosEIsNOR_Late=[89,90,91,92,96,97,98,101,102,103,105,106,107,108,109], numbersList(157,208,PosEIsDay14), %PosEIsDay14=[202,203,204,205,207,208,209,211,216,221,222,226,228,230,232,235,238,239,240,242,244,246,248,250,252,255,257], NegEIs=[], cover(PosEIsDay14,NegEIs,[],FinalTI), statistics(cputime,[Total2,Now]), TimeTaken is Now-Previous, write('Final Learning Result'),nl, tInterpreter(FinalTI,FinalT), print_list(FinalT), tCompScore(FinalTI,DL),write(DL), %write('Total Time Taken is '), %write(TimeTaken), told. /*lv:- numbersList(1,60,PosEIsDay1), cross_validation(PosEIsDay1,PA1), nl,write('Predictive Accurracy '),write(PA1),nl,nl, numbersList(61,120,PosEIsDay3), cross_validation(PosEIsDay3,PA2), nl,write('Predictive Accurracy '),write(PA2),nl,nl, numbersList(121,180,PosEIsDay7), cross_validation(PosEIsDay7,PA3), nl,write('Predictive Accurracy '),write(PA3),nl,nl, numbersList(181,240,PosEIsDay14),AllEIs=PosEIsDay14, cross_validation(AllEIs,PA), nl,write('Predictive Accurracy '),write(PA). */ lv:- numbersList(1,52,PosEIsDay1), cross_validation(PosEIsDay1,PA1), nl,write('Predictive Accurracy '),write(PA1),nl,nl, numbersList(53,104,PosEIsDay3), cross_validation(PosEIsDay3,PA2), nl,write('Predictive Accurracy '),write(PA2),nl,nl, numbersList(105,156,PosEIsDay7), cross_validation(PosEIsDay7,PA3), nl,write('Predictive Accurracy '),write(PA3),nl,nl, numbersList(157,208,PosEIsDay14),AllEIs=PosEIsDay14, cross_validation(AllEIs,PA), nl,write('Predictive Accurracy '),write(PA). /*tell('cancer_cv_day14.txt'), numbersList(157,208,PosEIsDay14), %PosEIsDay14=[202,203,204,205,207,208,209,211,216,221,222,226,228,230,232,235,238,239,240,242,244,246,248,250,252,255,257], PosEIs=PosEIsDay14, leaveOneOut(PosEIs,PosEIs,Results), % Results is a list of Uncovered test data -- you may trace the learning result and see why percentage(Results,PosEIs,PA), %sumList(Results,TotalA),length(Results,TotalN),PA is TotalA/TotalN, nl, %write('PA is '), write(PA), nl, %percentage(Results,PosEIs,PA), write('Predictive Accuracy is'),write(PA),nl, told, nl. */ forAll(P,Q):- \+ (P, \+Q). g:- tell('cancer_H_for_each_example.txt'), statistics(cputime,[Total1,Previous]), numbersList(157,208,PosEIs), %PosEIs= [1,3,4,5,6,7,8,9,10,11,12], forAll(member(EI,PosEIs),(nl,write(EI),nl,g(EI,T))), statistics(cputime,[Total2,Now]), TimeTaken is Now-Previous, write('Total Time Taken is '), write(TimeTaken), told. lv1:- % removed those covered by default noChange first. tell('cancer_23E_removeCovered.txt'), AllEI0=[1,2,3,4,5,6,7,8,9,10,11,12,14,15,16,17,18,19,20,22,23,24],%[1,4,5,7,10,11], %[1,3,4,5,6,7,8,9,10,11], asserta((enzyme_state(EC_Number,no_change):- (\+enzyme_state(EC_Number,inhibited);\+enzyme_state(EC_Number,activated))),Ref_defaultNoChangeStatement), unCoverRecord(AllEI0,AllEI), % reduce = remove those already explained by the examples erase(Ref_defaultNoChangeStatement), length(AllEI,PK), leaveOneOut(AllEI,AllEI,Results), % Results is a list of Uncovered test data -- you may trace the learning result and see why percentage(Results,AllEI,PA), write('Predictive Accuracy is'),write(PA),nl, told. lv:- tell('cancer_23E_LeaveOneOut.txt'), %findall(EIp,ex(EIp,Ep,1),PosEI0s), % full size learning %findall(EIn,ex(EIn,En,0),NegEIs), %length(NegEIs,NK), %unCoverRecord(PosEI0s,PosEIs), % reduce = remove those already explained by the examples %length(PosEIs,PK), /* PosEIs0=[1,3,4,5,6,7,8,9,10],%numbersList(1,100,PosEIs0), unCoverRecord(PosEIs0,PosEIs),write('Positive examples to be learned'),write(PosEIs),nl, %PosEIs=PosEIs0, NegEIs=[], append(PosEIs,NegEIs,AllEI),%write({PK,NK}),write('Totally '),nl, */ AllEI=[1,2,3,4,5,6,7,8,9,10,11,12,14,15,16,17,18,19,20,22,23,24], %[1,2,3,4,5,6,7,10,11,12,14,15,16,17,18,19,20,22,23,24],%[1,4,5,7,10,11], %[1,3,4,5,6,7,8,9,10,11], leaveOneOut(AllEI,AllEI,Results), % Results is a list of Uncovered test data -- you may trace the learning result and see why percentage(Results,AllEI,PA), write('Predictive Accuracy is'),write(PA),nl, told. % choose by counting co:- tell('cancer_H_for_23exs.txt'), statistics(cputime,[Total1,Previous]), %numbersList(1,13,PosEIs), PosEIs= [1,2,3,4,5,6,7,8,9,10,11,12,14,15,16,17,18,19,20,22,23,24], %[1,2,3,4,5,6,7,8,9,10,11,12], %forAll(member(EI,PosEIs),(nl,write(EI),nl,g(EI,T))), genAll_EIsigned(PosEIs,AllTs,TotalNum),write('Total is '), write(TotalNum),nl, lazyAllTsTranslation(AllTs,NewAllClas), length(AllTs,K),write('Number generalized is'), write(K),nl, %print_list(NewAllClas),nl, rb_new(Tree0), counting(NewAllClas,Tree0,Tree), rb_visit(Tree,Ts),%print_list(Ts),nl, %maplist(scoreCountedT,Ts,ScoredTs), %sort(ScoredTs,SortedScoredTs), %print_list(SortedScoredTs),nl, nl,nl,nl,write('Following, new results'),nl, chooseH(PosEIs,Ts,[],FinalH), print_list(FinalH),nl, statistics(cputime,[Total2,Now]), TimeTaken is Now-Previous, write('Total Time Taken is '), write(TimeTaken), told. tc:- PosEIs= [1,2,3,4,5,6,7,8,9,10,11,12,14,15,16,17,18,19,20,22,23,24], trainANDcount(PosEIs,FinalTI), tInterpreter(FinalTI,FinalT), write('*** Learning Result is'), nl,print_list(FinalT),nl. writeReaction(ReactionID):- (catalyzed_by_ECclass(ReactionID,EC_Numbers)-> Foo=1; EC_Numbers='NOT annotated' ), findall(SID-Snames, (consumed_by(SID,ReactionID,'IMPD'), findall(Sname,concept_name(SID,Sname,true),Snames)), SIDs), findall(PID-Pnames, (produced_by(PID,ReactionID,'IMPD'), findall(Pname,concept_name(PID,Pname,true),Pnames)), PIDs), nl, writeq(ReactionID),write(' Catalyzed EC number is '),write(EC_Numbers),write(' Substrates are '),write(SIDs), write(' Products are '), write(PIDs). sg:- % scriptGenerator scriptExGenerator('day1',1,52), scriptExGenerator('day3',53,104), scriptExGenerator('day7',105,156), scriptExGenerator('day14',157,208).