in a network querying problem , one is given a small network , corresponding to a known pathway or a complex of interest . the goal is to identify similar instances in a large network , where similarity is measured in terms of sequence or interaction patterns . previous approaches to the query problem required precise information on the interaction pattern of the query and were usually limited to small queries ( 24 proteins ) . pathblast  a server for querying linear pathways within a protein  protein interaction ( ppi ) network ( 1)was subsequently extended to allow searching for more general structures ( 2 ) . a general framework for subnetwork querying was developed ( 3 ) , but it is applicable only to very small queries due to its complexity . two other methods are netmatch , a cytoscape ( 4 ) plugin implementing the work of ferro et al . ( 5 ) that utilizes fast heuristics for subgraph isomorphism to identify approximate matches of queries within a collection of networks , and netgrep ( 6 ) , a system for searching networks for patterns corresponding to small sets of proteins with specified attributes and topology . the torque server implements a novel method for querying protein networks that does not require information on the interconnections ( topology ) among the query proteins ( 7 ) ( figure 1 ) . this makes torque applicable in broader scenarios , such as querying complexes or pathways whose topologies are not completely known , or even when querying from species for which ppi information is not available . ( 8) also studied queries with no topology information , but since their method is enumerative it was applied to very small queries ( 24 proteins ) . it was tested extensively on hundreds of queries of known complexes from a variety of species ( 7 ) . it was shown to yield far more matches than the qnet topology - based approach ( 2 ) , while providing results that are highly functionally coherent . the network induced by the vertices labeled a , b , c , d and e is a match to the query , where vertex c is an insertion and query element 4 is deleted . ( a ) the query proteins ; ( b ) the queried network . colored vertices in the network match nodes of the same color in the query . the network induced by the vertices labeled a , b , c , d and e is a match to the query , where vertex c is an insertion and query element 4 is deleted . the torque web server implements the algorithms in ( 7 ) for querying protein sets across species . it combines three approaches : a dynamic programming method utilizing color coding , integer linear programming and a fast heuristic based on shortest paths . torque automatically selects the best method to apply at each stage and outputs the highest scoring match . scores are based on the underlying network structure , on interaction confidence values and on sequence similarities between matching proteins . the input for torque consists of : 
 a query set of proteins in species a;their protein sequences;a ppi network for species b;the sequences of the network proteins . a query set of proteins in species a ; their protein sequences ; a ppi network for species b ; the sequences of the network proteins . all inputs are in simple text format : 
 the query set can be entered directly as a comma - delimited or whitespace - delimited list.protein sequences are given in the standard fasta format.the ppi network is given as a text file , where each row represents an interaction and contains the ids of the interacting pair and a confidence value for it in the range [ 0 , 1 ] . the query set can be entered directly as a comma - delimited or whitespace - delimited list . the ppi network is given as a text file , where each row represents an interaction and contains the ids of the interacting pair and a confidence value for it in the range [ 0 , 1 ] . it is possible to use a single fasta file ( input 2 ) for many queries , if it contains the sequences for all proteins in all queries . when the query field is left blank , torque will use all the proteins in input 2 as the query . if input 1 contains uniprot protein ids ( www.uniprot.org ) , their sequences need not be entered in input 2 ; instead , torque automatically retrieves them from the uniprot database . for several target species , currently , the server supports this option for the three target species saccharomyces cerevisiae , drosophila melanogaster and homo sapiens . the user can indicate one of these target species instead of providing inputs 3 and 4 . the user can control two parameters of the algorithm , setting a trade - off between speed and sensitivity . the user can set the threshold for blast similarity ( e - value ) . by setting a lower threshold , less homologs will be identified for the query proteins , making the algorithm faster but less sensitive . the second parameter is a threshold for the confidence values of ppi network edges provided as part of input 3 . edges whose confidence value is lower than the threshold are discarded ; hence , this parameter determines the sparsity of the target network and affects the number of possible matches and the running time . the running time of torque is typically a few minutes , but may be up to an hour , depending on the size and other properties of the query ( for more details , see ( 7 ) ) . if several queries are submitted to the server at the same time , they are queued and executed sequentially . rather than waiting for the results online , they can be accessed later , in two ways : 
 when a torque job is started , it is assigned a nine - digit job i d . this i d can be used to access the results later from the main torque page.before submitting a query , the user may enter an email address . once torque has finished processing the query , the results will be sent to the email address provided . when a torque job is started , it is assigned a nine - digit job i d . this i d can be used to access the results later from the main torque page . before submitting a query once torque has finished processing the query , the results will be sent to the email address provided . the web server generates a web page ( figure 2 ) with the image of the top - scoring match for the query in the target network , as well as an auxiliary file in.sif format that can be viewed using the cytoscape software ( 4 ) . the content of the.sif file includes , for each edge , a numerical value representing the confidence in the interaction it represents , as provided in the input . the image shows the subgraph induced by the top - scoring match in the ppi network . each vertex is labeled with its protein name in the ppi network and its matching query protein , if such exists . insertion vertices are shown in gray , and proteins from the query for which there was no match in the solution ( deletions ) are listed separately . the following example uses as query the mouse dna synthesome complex , downloaded from the corum website ( http://mips.gsf.de/genre/proj/corum/index.html ) . this 13-member complex was queried in the yeast network ( 5430 proteins , 39 936 interactions ) . examining the subnetwork identified by torque we find that it is functionally coherent ( nucleotidyltransferase activity , p < 1.4e  10 ) and significantly intersects the yeast alpha dna polymerase : primase complex , supporting its biological plausibility . the input for torque consists of : 
 a query set of proteins in species a;their protein sequences;a ppi network for species b;the sequences of the network proteins . a query set of proteins in species a ; their protein sequences ; a ppi network for species b ; the sequences of the network proteins . all inputs are in simple text format : 
 the query set can be entered directly as a comma - delimited or whitespace - delimited list.protein sequences are given in the standard fasta format.the ppi network is given as a text file , where each row represents an interaction and contains the ids of the interacting pair and a confidence value for it in the range [ 0 , 1 ] . the query set can be entered directly as a comma - delimited or whitespace - delimited list . the ppi network is given as a text file , where each row represents an interaction and contains the ids of the interacting pair and a confidence value for it in the range [ 0 , 1 ] . it is possible to use a single fasta file ( input 2 ) for many queries , if it contains the sequences for all proteins in all queries . when the query field is left blank , torque will use all the proteins in input 2 as the query . if input 1 contains uniprot protein ids ( www.uniprot.org ) , their sequences need not be entered in input 2 ; instead , torque automatically retrieves them from the uniprot database . for several target species , currently , the server supports this option for the three target species saccharomyces cerevisiae , drosophila melanogaster and homo sapiens . the user can indicate one of these target species instead of providing inputs 3 and 4 . the user can control two parameters of the algorithm , setting a trade - off between speed and sensitivity . the user can set the threshold for blast similarity ( e - value ) . by setting a lower threshold , less homologs will be identified for the query proteins , making the algorithm faster but less sensitive . the second parameter is a threshold for the confidence values of ppi network edges provided as part of input 3 . edges whose confidence value is lower than the threshold are discarded ; hence , this parameter determines the sparsity of the target network and affects the number of possible matches and the running time . the running time of torque is typically a few minutes , but may be up to an hour , depending on the size and other properties of the query ( for more details , see ( 7 ) ) . if several queries are submitted to the server at the same time , they are queued and executed sequentially . rather than waiting for the results online , they can be accessed later , in two ways : 
 when a torque job is started , it is assigned a nine - digit job i d . this i d can be used to access the results later from the main torque page.before submitting a query , the user may enter an email address . once torque has finished processing the query , the results will be sent to the email address provided . when a torque job is started , it is assigned a nine - digit job i d . this i d can be used to access the results later from the main torque page . before submitting a query once torque has finished processing the query , the results will be sent to the email address provided . the web server generates a web page ( figure 2 ) with the image of the top - scoring match for the query in the target network , as well as an auxiliary file in.sif format that can be viewed using the cytoscape software ( 4 ) . the content of the.sif file includes , for each edge , a numerical value representing the confidence in the interaction it represents , as provided in the input . the image shows the subgraph induced by the top - scoring match in the ppi network . each vertex is labeled with its protein name in the ppi network and its matching query protein , if such exists . insertion vertices are shown in gray , and proteins from the query for which there was no match in the solution ( deletions ) are listed separately . the following example uses as query the mouse dna synthesome complex , downloaded from the corum website ( http://mips.gsf.de/genre/proj/corum/index.html ) . this 13-member complex was queried in the yeast network ( 5430 proteins , 39 936 interactions ) . examining the subnetwork identified by torque we find that it is functionally coherent ( nucleotidyltransferase activity , p < 1.4e  10 ) and significantly intersects the yeast alpha dna polymerase : primase complex , supporting its biological plausibility . the torque web server allows users to run topology - free queries on predefined or user - provided target networks . the result is a subnetwork of the target network most similar to the query , and is presented both graphically and as a downloadable text file . ) ; german - israel foundation grant ( to r.s . ) ; postdoctoral fellowship from the edmond j. safra bioinformatics program at tel aviv university ( to f.h . ) . funding for open access charge
torque is a tool for cross - species querying of protein 
 protein interaction networks . it aims to answer the following question : given a set of proteins constituting a known complex or a pathway in one species , can a similar complex or pathway be found in the protein network of another species ? to this end , torque seeks a matching set of proteins that are sequence similar to the query proteins and span a connected region of the target network , while allowing for both insertions and deletions . unlike existing approaches 
 , torque does not require knowledge of the interconnections among the query proteins . 
 it can handle large queries of up to 25 proteins . 
 the torque web server is freely available for use at http://www.cs.tau.ac.il/bnet/torque.html .