gopubmed and beyond: rules and reasoning for ontology-based literature search

Michael Schroeder BioTechnological CenterTU [email protected]://www.biotec.tu-dresden.de Biotec

GoPubMed and beyond: Rules and reasoning for

ontology-based literature search

By Michael Schroeder, Biotec, 2003 2

REWERSE:a European Network of Excellence

Reasoning on the Web with Rules and Semantics Technology

Rule Markup languages Policy specification, composition and conformance Composition and typing Reasoning-aware querying Evolution and reactivity

Application Web-based Decision Support for Event, Temporal, and Geographical

Data Towards a Bioinformatics Semantic Web Personalised Information Systems

Towards a Bioinformatics Semantic Web Groups: Dresden, Jena, Lisbon, Linkoeping, Edinburgh, Bucarest,

Manchester, Paris Rules and constraints for structure prediction, metabolic pathways, gene

expression analysis, ontologies, workflows.


Problem

PubMed >12M articles


Example Task Which enzymes does Levamisole inhibit?

It is well known that Levamisole inhibits alkaline phosphatase

It is not well known that Levamisole inhibits phosphofructokinase


PubMed Example A keyword search for

levamisole inhibitor produces well over 100 hits in PubMed.

To find out about specific functions, we have to go through all these papers!

We are interested in the relevant enzymatic functions.

A refined search for Levamisole inhibitor enzymatic activity produces only 5 hits - a lot of relevant papers have been dropped.


GoPubMed Example

Query: Levamisole inhibitor

Maximum papers: 100Strict matching

54 papers in biological process20 in cellular components72 in molecular function


GoPubMed Example

Let’s look for some functions:

70 papers including terms, which are enzyme activities


GoPubMed Example

Transferase 8Kinase 6Hydrolase 58Oxidoreductase 2Lyase 1


GoPubMed Example

Alkaline Phosphatase:

52 papers

…alkaline phosphatase

inhibitor levamisole…

Effects of alkaline

phosphatase and its

inhibitor Levamisole…


GoPubMed Example

Phosphofructokinase


GoPubMed Example

Levamisole direclty inhibits tumor

phosphofructokinase


GoPubMed Example

In PubMed the article is listed at position 84!And hence unlikely to

be read


Prova


Prova Rule-based Java scripting for middleware Combination of object-oriented and declarative

programming Offer a rule-based platform for distributed

agent programming. Expose logic and agent behaviour as rules; Access data sources via wrappers written in Java Make all Java API from available packages

directly accessible from rules; Run within the Java runtime; Enable rapid prototyping of applications;


PubMed XML Output<PubmedArticle> <MedlineCitation Owner="NLM" Status="Publisher"> <PMID>15469972</PMID> <DateCreated> <Year>2004</Year> <Month>10</Month> <Day>7</Day> </DateCreated> <Article> <Journal> <ISSN>0950-1991</ISSN> <JournalIssue PrintYN="N"> <PubDate> <Year>2004</Year> <Month>10</Month> <Day>6</Day> </PubDate> </JournalIssue> <Coden>DEVPED</Coden> <Title>Development (Cambridge, England)</Title> <ISOAbbreviation>Development</ISOAbbreviation> </Journal>…


Output

Year: 2004ArticleTitle: Developmental potential of defined neural progenitors derived from mouse embryonicstem cells.LastName: PlachtaFirstName: NicolasInitials: N**********************LastName: BibelFirstName: MiriamInitials: M**********************LastName: TuckerFirstName: Kerry LeeInitials: KL**********************LastName: BardeFirstName: Yves-AlainInitials: YA******************************************Year: 2004ArticleTitle: Eye evolution: a question of genetic promiscuity.LastName: NilssonForeName: Dan-EInitials: DE**********************…


Code Snippet%%% XML reading tests

:- eval(test_xml1()).

test_xml1() :-Document=XML("pubmed.xml"),Root = Document.getDocumentElement(),tagname(Root,Elements),

Elements.nodes(Element),subtag(Element,SubElements),

SubElements.nodes(SubElement), SubElementNodeName = SubElement.getNodeName(),

ChildNodes=SubElement.getChildNodes(),ChildNodes.nodes(ChildNode),evaluate(ChildNode).

tagname(Root,Elements):- Elements =

Root.getElementsByTagName("MedlineCitation").

subtag(Element,SubElements):- SubElements =

Element.getElementsByTagName("PubDate").subtag(Element,SubElements):- SubElements =

Element.getElementsByTagName("Article").subtag(Element,SubElements):- SubElements =

Element.getElementsByTagName("Author").

evaluate(ChildNode):- "Year"=ChildNode.getNodeName(), printout(ChildNode).

evaluate(ChildNode):- "Initials"=ChildNode.getNodeName(), printout(ChildNode), println([**********************]).evaluate(ChildNode):- "FirstName"=ChildNode.getNodeName(), printout(ChildNode).evaluate(ChildNode):- "ForeName"=ChildNode.getNodeName(), printout(ChildNode).evaluate(ChildNode):- "LastName"=ChildNode.getNodeName(), printout(ChildNode).evaluate(ChildNode):- "ArticleTitle"=ChildNode.getNodeName(), printout(ChildNode).

printout(ChildNode):-ChildNodeName = ChildNode.getNodeName(),DataName = ChildNode.getFirstChild(),StringName = DataName.getNodeValue(),println([ChildNodeName, ": ",StringName]).

Prolog rules

Javaobjects

Unification


Traverse the GO tree and find all phosphofructokinases

:-eval(consult("utils.prova")).

location(database,“go","jdbc:mysql://comas.soi.city.ac.uk","guest","guest").location(database,"GO","jdbc:mysql://dbserver","guest","guest").

:-solve(isPhosphofructokinase()).

isPhosphofructokinase() :- dbopen("GO",DB), println(["DB open"]), sql_select(DB,term,[id,TermID],[name,Name],[where,"name = 'phosphofructokinase activity'"]), println(["Looking for all children of GO-Term (",TermID,"): ",Name]), findall(TermID,isPhosphofructokinase(DB,TermID),_).

isPhosphofructokinase(DB,TermID) :- concat(["term1_id=",TermID],WhereClause), sql_select(DB,term2term,[term2_id,ChildTermID],[where, WhereClause]), concat(["id=",ChildTermID],WhereClause2), sql_select(DB,term,[name,ChildName],[where,WhereClause2]), println([TermID," has child ", ChildName,",",ChildTermID]), isPhosphofructokinase(DB,ChildTermID).

isPhosphofructokinase(DB,TermID) :- println([TermID," does not have any children."]).

Backtracking

Built-in DB access

Built-in DB access

Recursion


OutputLooking for all children of GO-Term (2153): phosphofructokinase

activity2153 has child 1-phosphofructokinase activity,21542154 does not have any children.2153 has child 6-phosphofructo-2-kinase activity,21552155 does not have any children.2153 has child 6-phosphofructokinase activity,21562156 does not have any children.2153 does not have any children.yes


Messaging and Reaction Rules Prova is designed to implement agents in a

distributed system Prova is based on theoretical work on multi agent

systems

Prova provides predicates to send and receive messages and to realise reaction rules


Code Snippet:- eval(ex004()).

a(1).a(2).b(3).b(4).

% Send out messagesex004() :-

println(["==========ex004=========="]),iam(Me),

sendMsg(XID1,self,Me,queryref,a(I)),rcvMult(XID1,self,Me,reply,a(I)),println(["Inline reaction ",rcvMult(XID1,self,Me,reply,a(I))]),

sendMsg(XID2,self,Me,queryref,b(J)),rcvMult(XID2,self,Me,reply,b(J)),println(["Inline reaction ",rcvMult(XID2,self,Me,reply,b(J))]).

% Reaction rule to general queryrefrcvMsg(XID,Protocol,From,queryref,[X|Xs]|LocalContext) :-

println(["Rule reaction 1 ",rcvMsg(XID,Protocol,From,queryref,[X|Xs]|LocalContext)]),derive([X|Xs]),sendMsg(XID,Protocol,From,reply,[X|Xs]|LocalContext).

rcvMsg(XID,Protocol,From,queryref,[X|Xs]|LocalContext) :-println(["Rule reaction 2 ",rcvMsg(XID,Protocol,From,queryref,[X|Xs]|LocalContext)]),sendMsg(XID,Protocol,From,end_of_transmission,[X|Xs]|LocalContext).

% A testing harness for printing incoming end_of_transmission messages.rcvMsg(XID,Protocol,From,end_of_transmission|Extra) :-

println(["end_of_transmission for conversation-id ",XID,": "|Extra]).

Built-in agent agent communication:

sendMsg and rcvMsg

Abstracting from protocols like JMS, Jade or inline


Output==========ex004==========Rule reaction 1 ["rcvMsg","mediator@bioinf-mobile3","self","mediator","queryref",["a",I]]Rule reaction 2 ["rcvMsg","mediator@bioinf-mobile3","self","mediator","queryref",["a",I]]Inline reaction ["rcvMult","mediator@bioinf-mobile3","self","mediator","reply",["a",1]]Inline reaction ["rcvMult","mediator@bioinf-mobile3","self","mediator","reply",["a",2]]end_of_transmission for conversation-id mediator@bioinf-mobile3: ["a",I]Rule reaction 1 ["rcvMsg","mediator@bioinf-mobile6","self","mediator","queryref",["b",N@@16]]Rule reaction 2 ["rcvMsg","mediator@bioinf-mobile6","self","mediator","queryref",["b",N@@16]]Rule reaction 1 ["rcvMsg","mediator@bioinf-mobile8","self","mediator","queryref",["b",N@@16]]Rule reaction 2 ["rcvMsg","mediator@bioinf-mobile8","self","mediator","queryref",["b",N@@16]]Inline reaction ["rcvMult","mediator@bioinf-mobile6","self","mediator","reply",["b",3]]Inline reaction ["rcvMult","mediator@bioinf-mobile6","self","mediator","reply",["b",4]]end_of_transmission for conversation-id mediator@bioinf-mobile6: ["b",N@@16]Inline reaction ["rcvMult","mediator@bioinf-mobile8","self","mediator","reply",["b",3]]Inline reaction ["rcvMult","mediator@bioinf-mobile8","self","mediator","reply",["b",4]]end_of_transmission for conversation-id mediator@bioinf-mobile8: ["b",N@@16]end_of_transmission for conversation-id mediator@bioinf-mobile3: ["a",I]Shutdown complete.


Conclusion GoPubMed facilitates exploration of literature abstracts with the

GeneOntology Prova implements Prolog-style rules and reasoning with Java

Thanks: GoPubMed: Andreas Doms, Ralf Delfs, Alex Kozlenkov Prova: Alex Kozlenkov Support: EU Projects REWERSE, GeneStream, BioGrid

Contact: Michael Schroeder: [email protected]

URLs www.biotec.tu-dresden.de www.rewerse.net (REWERSE project including info on bioinfo group) www.semanticwebrules.org (Prova) www.gopubmed.org (GoPubMed)

gopubmed and beyond: rules and reasoning for ontology-based literature search

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