the integration of genomic sequences with transcription factor function and gene expression to decipher the gene regulatory networks underlying various developmental processes is a major challenge of the post - genomic era ( 1 ) . although the view that regulatory regions manifest as clusters of transcription factor binding sites ( tfbss ) has been around for some time , it was the review by arnone and davidson ( 2 ) that clearly presented the case for emphasizing cis - clusters in both experimental and computational analyses .
in fact , it is this paradigm shift that led to important advances in the detection of combinatorial occurrence of cis - elements and understanding transcriptional regulation ( 3 ) .
however , the availability of a number of completely sequenced eukaryotic genomes with an ever expanding volume of gene expression profile data has made computationally based strategies for deciphering genetic regulatory networks more viable .
the methods range from sophisticated gibbs sampling - based algorithms to more  brute force counting and analysis of fixed - length oligonucleotide words ( kmer or ktuple word searching ) ( 4,5 ) . for a complete list of internet resources and tools available to predict transcription regulatory clusters ,
computational methods have focused primarily on trying to identify the co - occurrence of a set of tfbss in a group of genes co - expressed or functionally related , and most of them have been restricted to the promoter or upstream regions .
however , the basic problem of identifying the true positives from a list of combinatorial patterns remains .
the problem becomes even more complicated and the results are difficult to interpret when the entire stretch of non - coding regions comprising introns and upstream and downstream regions is considered .
adopting a phylogenetic approach allows substantial reduction in the number of false positives in the identification of regulatory regions of individual orthologous gene pairs ( 712 ) .
although the need for experimental validation remains critical , at present , predicted cis - acting signature element searches can greatly focus experimental targets for validation studies .
the detection of a particular known cis - acting element in all or many of the genes in a particular expression cluster does not necessarily mean that the genes are regulated via that element .
the likelihood of this prediction is greater if each of these shared clusters is also conserved in the corresponding inter - species ortholog .
cismols analyzer is built based on these two hypotheses and is designed to identify significant cis - regulatory elements from sets of co - expressed or related groups of genes for elements that are also ortholog - conserved .
to do this , ortholog - conserved cis - clusters for each individual gene pair are identified and stored in the database .
next , a gene list is compiled based on various criteria such as coordinate regulation and then the ortholog - conserved cis - clusters for each of the genes in the list are compared to identify occurrence of common cis - clusters . since the existence of gene regulatory regions in intronic and downstream regions is well proven , our method to identify these sites is not confined to upstream regions alone , but is extended to intronic and 5 and 3 gene - flanking regions .
we have successfully validated our algorithm on several data sets comprising skeletal muscle - specific genes , liver - specific genes , pancreas overexpressed genes , olfactory genes ( 13 ) and immune system genes ( 14 ) .
genomic regions of orthologous genes are retrieved from ucsc golden path , along with the exon annotations .
putative regulatory regions are identified either by using our earlier developed trafac server ( 12 ) or by searching against the potential regulatory regions stored in the genometrafac database (; jegga et al .
the conserved cis - element dense regions for each of the ortholog gene pairs are compared to identify the common binding sites in a group of genes .
researchers can automatically ( i ) create gene groups and identify shared ortholog - conserved putative regulatory regions and individual binding sites , ( ii ) search genes for known cis - regulatory modules and ( iii ) identify potential novel gene targets for known cis - regulatory modules or novel clusters of individual binding sites .
cismols analyzer is designed to analyze a list of genes  typically co - expressed or related genes  for cis - element clusters that are shared by genes in the list .
in contrast , genometrafac is a whole - genome repository of individual genes with specified gene orthologs that have been analyzed , in batch form over the entire genome , for phylogenetically conserved cis - elements ( jegga et al . , manuscript submitted ) .
trafac is similarly single - gene oriented , but it allows for the entry of human - curated ortholog gene pairs ( 12 ) .
cismols analyzer operates on genes in either database by allowing lists of these genes to be formed and then subjecting the lists to shared cis - element analysis .
it is possible to analyze existing gene groups that have been assembled by the system administrators and by other users .
however , to create new groups and perform a clustering analysis to detect modules that contain shared cis - elements , a login account is needed .
options are also provided to select the genomic regions for a single gene or a group of genes that need to be searched for the occurrence of common tfbss . by default , cismols analyzer searches for clusters in the genomic region comprising the 5- and 3-flanking 10 kb and also the intronic regions . after submitting the genes for analysis
, the user will be notified by email of the availability of the results when the clustering is finished .
users can customize the search criteria using boolean logic to restrict the search to known validated cis - regulatory modules and/or a combination of individual binding sites . the minimum number of binding sites that must appear in each cluster , or the minimum number of genes in which each cluster must appear , can also be specified .
cismols analyzer is designed to analyze a list of genes  typically co - expressed or related genes  for cis - element clusters that are shared by genes in the list .
in contrast , genometrafac is a whole - genome repository of individual genes with specified gene orthologs that have been analyzed , in batch form over the entire genome , for phylogenetically conserved cis - elements ( jegga et al . , manuscript submitted ) .
trafac is similarly single - gene oriented , but it allows for the entry of human - curated ortholog gene pairs ( 12 ) .
cismols analyzer operates on genes in either database by allowing lists of these genes to be formed and then subjecting the lists to shared cis - element analysis .
it is possible to analyze existing gene groups that have been assembled by the system administrators and by other users .
however , to create new groups and perform a clustering analysis to detect modules that contain shared cis - elements , a login account is needed .
options are also provided to select the genomic regions for a single gene or a group of genes that need to be searched for the occurrence of common tfbss . by default , cismols analyzer searches for clusters in the genomic region comprising the 5- and 3-flanking 10 kb and also the intronic regions . after submitting the genes for analysis
, the user will be notified by email of the availability of the results when the clustering is finished .
users can customize the search criteria using boolean logic to restrict the search to known validated cis - regulatory modules and/or a combination of individual binding sites .
the minimum number of binding sites that must appear in each cluster , or the minimum number of genes in which each cluster must appear , can also be specified .
the output generated is a set of putative regulatory modules occurring within an ortholog conserved region of two or more genes .
cismolgram ( figure 1 ) , a graphical representation of ortholog - conserved cis - clusters shared by a group of genes , depicts the location of clusters within gene regions .
the shared cis - clusters ( two or more than two binding sites ) are represented as variously colored boxes on the gene .
each of these shared clusters is linked to its respective ortholog conserved regions and can be visualized as trafacgrams or regulograms ( described in the legend of figure 1 ) .
the trafac and regulogram image pages have the option to download the sequences ( corresponding to that cluster window ) in fasta format .
links are also provided to the human and mouse ucsc browser , in which the user can see a cismols - identified cluster in the context of other annotations .
users can also download the ucsc browser - compatible gff files ( currently gff3 ) for each sequence from the regulogram image page .
these can be uploaded directly to ucsc golden path , enabling visualization of the cismols cluster region in the context of all other features available as aligned annotation tracks ( known genes , predicted genes , ests , mrnas , cpg islands , assembly gaps and coverage , chromosomal bands , other species homologies and more ) .
the table view or the legend ( figure 1d ) displays a summary of the results .
it indicates the details of each cluster ( the individual constituent cis - elements and their total frequency ) and the frequency of the clusters occurring in each of the genes compared and involved in cluster analysis .
the default base sequence is the human gene , and it is mapped to the corresponding mouse ortholog . however , the program can be used for any ortholog gene pair after uploading their alignments and binding sites to the trafac database .
options are also provided to modify the viewable regions to focus on cis - clusters of interest .
the cismolgram can be saved or exported as images ( svg , tiff , pdf , png or jpg format ) .
the time taken to analyze a group of genes depends upon factors such as number of genes in the group , gene lengths , percentage conservation between the orthologous pair of genes , and ortholog - conserved cis - element clusters .
cismols analyzer looks for conserved cis - element clusters within conserved regions [ blastz - aligned genomic regions of 70% sequence similarity ( 15 ) ] .
matinspector ( 16 ) is used to identify the potential binding sites in each of the genomic sequences . the analysis parameters for identification of tfbss
were set to 0.85 for the core similarity and optimal for the matrix similarity . a typical analysis on the cismols server  for , say , 50 ortholog gene pairs with default parameter settings of 10 kb upstream and downstream for each gene
 takes approximately 1 h. the current upper limit of processing capability is about 242 ortholog gene pairs ( a total sequence length of 32 mb , of which about 7 mb are blastz - aligned with 70% sequence similarity ) .
currently we are also working on providing the statistical significance and comparison between cis - clusters identified for two discrete gene groups .
most of the time , the cis - element clusters responsible for tissue specificity tend to be scored relatively low .
for example , searching for ortholog - conserved shared cis - clusters in a group of pancreas overexpressed genes without any cis - element filter resulted in the identification of non - specific clusters . however , when the search was performed again restricting the results to only those clusters that have at least one pdx binding site , the resulting shared clusters coincided with the validated regulatory regions of each of the individual genes ( data not shown ) .
the top hits , or the cis - element clusters shared by the most genes , tend to be more general , and , although they are important for gene expression , very little knowledge can be extracted from these about conferring tissue specificity for a group of genes .
using a control or a negative control does , however , improve understanding of the importance of the shared clusters  for instance , comparing the most shared cis - clusters in a group of genes with overexpression in the liver with genes overexpressed in the cerebellum .
clearly , there is a paradox in the phylogenetic footprinting approach . to allow the recognition of conserved ( regulatory ) elements
, there should be enough evolutionary distance , but , at the same time , this evolutionary distance makes it difficult to recognize tfbss  the short conserved elements
. nevertheless , the significance of a predicted shared cis - regulatory module for a group of co - expressed genes or a functionally related group of genes will be higher if the shared clusters are additionally conserved in both gene orthologs .
detection and visualization of compositionally similar cis - regulatory modules shared by multiples genes . ( a ) cismolgram provides a depiction of cis - element modules that are shared across two or more genes and contain two or more binding sites .
each module is represented by variously colored boxes located relative to the promoter of each gene in the analyzed group .
genes gathered from the genometrafac database generally have their first exon locations at position 40 000 .
the locations of the clusters can be selected to be shown over either set of gene orthologs . by clicking on a cluster module ( circled ) ,
a link is given to view either ( b ) the density of conserved elements over the regions ( regulogram ) or ( c ) the conserved cis - element arrangement at that location ( trafac image ) .
the regulogram shows the two sequences , mouse and human , represented as horizontal bars .
the green - colored bars shown parallel to the genomic sequences represent the repeat regions .
the regions of sequence alignment are represented as differently colored quadrilaterals that relate one sequence to another . within each shaded block ,
the percentage sequence similarity and the number of tfbss are represented as two separate line graphs in the lower half .
the frequencies of individual binding sites occurring in each of the sequences separately are shown as two running graphs in the top half of the pane .
the percentage similarity is the average sequence conservation as determined by the blastz algorithm and the shared cis - element hits are determined by an algorithm that uses a 200 bp moving window to look through the cis - elements present within the conserved sequence block .
the regulogram can be clicked to zoom in or to view the tfbss that are common to the two sequences at the click - point coordinate . in the trafac image ,
the two gray vertical bars are the two genes ( human and mouse ) compared .
the tfbss occurring in both the genes are highlighted as variously colored bars drawn across the two genes .
( d ) the table view or the cismolgram legend displays a summary of the results .
it indicates the details of each cluster ( the constituent individual cis - elements and their total frequency ) and the frequency of the clusters occurring in each of the genes compared and involved in cluster analysis .
 combinatorial interactions of sequence - specific trans - acting factors with localized genomic cis - element clusters are the principal mechanism for regulating tissue - specific and developmental gene expression . with the emergence of expanding numbers of genome - wide expression analyses , the identification of the cis - elements responsible for specific patterns of transcriptional regulation represents a critical area of investigation . 
 computational methods for the identification of functional cis - regulatory modules are difficult to devise , principally because of the short length and degenerate nature of individual cis - element binding sites and the inherent complexity that is generated by combinatorial interactions within cis - clusters . 
 filtering candidate cis - element clusters based on phylogenetic conservation is helpful for an individual ortholog gene pair , but combining data from cis - conservation and coordinate expression across multiple genes is a more difficult problem . to approach this , 
 we have extended an ortholog gene - pair database with additional analytical architecture to allow for the analysis and identification of maximal numbers of compositionally similar and phylogenetically conserved cis - regulatory element clusters from a list of user - selected genes . 
 the system has been successfully tested with a series of functionally related and microarray profile - based co - expressed ortholog pairs of promoters and genes using known regulatory regions as training sets and co - expressed genes in the olfactory and immunohematologic systems as test sets . 
 cismols analyzer is accessible via a web interface at . 
INTRODUCTION
INPUT
Creating and submitting gene groups for analysis
Searching for 
OUTPUT
SOFTWARE AND ACCESS
CONCLUSION
Figures and Tables