BACKGROUND
techniques such as microarray analysis allow measurements of the differential gene expression in cells for tens of thousands of genes simultaneously.
the ability to measure changes in the transcription activity of a cell in response to an external stimulus allows for a system-wide approach in which pathways and sub-networks are analyzed rather than the activity of isolated genes  <cit> .
further, the development of biological knowledge systems such as the gene ontology   <cit>  have provided a framework in which groups of genes can be classified in three areas: biological processes, molecular function and cellular components.
this ontological classification scheme of gene function gives a hierarchical context in which groups of genes can be regarded to determine how closely they are functionally related  <cit> .
a complimentary approach to above classification based on go is the assessment of molecular functions in the context of known interactions between genes, dna/rnas, proteins and small chemicals, as mapped in biochemical interaction maps, pathways and networks  <cit> .
the novel combination of these biochemical networks, along with the classifications provided by the go, allows important clusters of genes in the cellular response to be identified.
it further provides evidence by adjacency and pathway connectivity to assign genes that may not be significantly expressed to the relevant gene clusters.
here, these methods are used to study properties of avian influenza infection with h5n <dig> virus, and to compare this infection to another upper respiratory tract infection, namely respiratory syncytial virus .
the h5n <dig> influenza virus shows remarkably higher virulence than other strains of influenza  <cit> .
a greater understanding of the h5n <dig> virus is motivated by epidemiological concerns, particularly in-light of the recent emergence of the h1n <dig> strain, because it is a prime candidate as a future pandemic infection should it mutate or reassort into a form that can be easily contracted by humans  <cit> .
as a cross check on the significance analysis, a support vector machine  algorithm  <cit>  is used to identify which genes show the greatest differences in their expressions between the h5n <dig> infected and control samples.
this ranking is then compared to the significance analysis and genes associated with over represented go nodes as well as genes that are closely associated with significant genes through interactions in the human network.
this cross check will allow us to identify nodes that are not properly annotated, thus are not captured by the go analysis.
RESULTS
results are presented in threefold.
first, significant clustering of genes into sub-graphs of the gene ontology are identified using the go enrichment analysis plugin bingo  <cit>  for cytoscape  <cit> .
second, many of the most strongly up and down regulated genes are examined and their possible function in the cellular response of normal human bronchial epithelial  cells to h5n <dig> is considered with comparison to rsv and mock infections.
comparisons were made at  <dig> and  <dig> hours postinfection for comparison of gene expression changes prior to and following productive viral replication, generally 12- <dig> hours postinfection in this nhbe culture model.
viral replication was verified by standard plaque assay techniques under the appropriate biocontainment levels.
a total of  <dig> and  <dig> genes were found to be both significant biologically and statistically post infection at  <dig> and  <dig> hours, respectively.
of these, only a small fraction are associated with over represented go nodes.
third, human response networks are calculated and correlated with go.
significant sub-graphs
after  <dig> and  <dig> hours of h5n <dig> exposure,  <dig> and  <dig> significant genes relative to the controls were identified, respectively.
in spite of  <dig> genes being found at  <dig> hours, no significant over-representation of any go nodes was found by bingo.
at  <dig> hours after infection, several go nodes showed over-representation and are listed in table  <dig> along with the significant genes that are annotated with the corresponding go id.
only nodes that are significant at the  <dig>  level using a bonferroni correction are listed.
using the more liberal benjamini correction did not yield appreciably different graphs  <cit> .
the genes associated with each of these go nodes and their functional interactions with other genes as described by our constructed human network are shown in figure  <dig> .
most of the genes in the go clustering and those found associated/related in the human network are up-regulated, with a minority being down-regulated.
many of the genes with the greatest change in expression, however, were down regulated such as egr <dig>  fos and egr <dig> as shown in table  <dig> .
the most significant go nodes are given with their raw p-values.
under each go entry is a list of the genes associated with that node.
errors are based on the variation of the fold change in expression between the three independent trials.
egr <dig> has the greatest average down-regulation of all genes observed in this study at both  <dig> and  <dig> hours with fos being more down-regulated than egr <dig> at  <dig> hours and fos and egr <dig> switching places at  <dig> hours.
the log <dig> fold changes are shown.
another visualization of these results is depicted in figure  <dig> , which contains a network that used daughters of bingo nodes as seeds for the human response network.
as a result there are many genes connected to each go node.
the increased number of paths between go nodes obscures the genes that are at the hub of activity, though fos, ifi <dig>  stat <dig>  cxcl <dig> and cdc <dig> are rather well connected.
this is in contrast to figure  <dig>  which shows a graph where the significant genes were used as seeds regardless of their go connections to generate a human response network, and the resulting graph was then merged with the go nodes found to be significant with bingo.
interestingly, no significant over-representation of go nodes can be found among the significantly represented genes during rsv infection.
that is, looking at the genes that are both biologically and statistically significant in the rsv but not in the mock assays.
this may indicate that the response to rsv at times earlier than  <dig> hours does not involve activating genes that are not part of the normal metabolic behavior of the cell.
it is possible that there is a more subtle interplay between the gene activations in how the cell orchestrates a response.
alternatively, the effects of early rsv infection could be small such that the cell has not mustered significant changes in gene expression by  <dig> hours post infection.
in any case, using the union of all genes found to be significant in any of the control experiments is rather conservative and may exclude sufficient true positives to make finding significantly over represented go nodes difficult; however, this also highlights the dramatic response of the cell to infection by h5n <dig>
genes of interest
although no significant go nodes are found at  <dig> hours, there is one sub-network associated with binding in the gene ontology that contains a fair number of genes.
at  <dig> hours this sub-network contains a handful of genes including ctgf, cyr <dig>  sdpr and lgals <dig>  by  <dig> hours this has expanded to accommodate numerous genes.
this parent node common to the genes of this subnetwork is associated with ifit <dig>  a gene that codes for an interferon induced protein.
other subnetwork that are easily identified by visual inspection include genes involving transcription regulation, with the genes egr <dig>  jun, mcm <dig>  fosb, fos and zfp <dig> being significantly regulated at both  <dig> and  <dig> hours, and genes involved with post transcriptional/translational modification such as tap <dig>  isg <dig>  and plk <dig>  there are also a number of kinase/phosphatase related genes, dusp <dig>  abcc <dig>  socs <dig>  among these, several of these genes also appear among the top  <dig> components to the vector normal to the ohp in the svm analysis.
table  <dig> lists genes from table  <dig> that appear as significant in the  <dig> and  <dig> hour experiments.
although most of these genes are not found in the bingo analysis, they are generally found to be highly connected to those genes through the human network.
many of these genes, including cyr <dig>  egr <dig>  jun and dusp <dig> are prominently displayed in the response network in figure  <dig>
genes are listed in order of importance in the svm analysis.
the fold change in each gene is the average fold change in gene expression including both the  <dig> and  <dig> hour data.
in the last two columns, a "+" indicates that the gene was found in both the significance and svm analyses at  <dig> or  <dig> hours, respectively.
a "-" indicates that the gene was not found in the results in both analyses at  <dig> or  <dig> hours.
genes through sfrs <dig> are among the top  <dig> and through the end of the list are in the top  <dig>
the components of the ohp in the svm analysis are displayed along with the average fold change of the gene in the h5n <dig> data and control data, and the average p-values in the h5n <dig> and control data.
the length of each component is also given.
a negative component to the vector normal to the ohp indicates a decrease in the fold change in gene expression from the control to the h5n <dig> exposures while a positive component indicates an increase in the differential expression from control to h5n <dig>
among the three most dramatically regulated genes at both  <dig> and  <dig> hours is the early growth response  <dig> gene egr <dig>  which is down-regulated by about an order of magnitude at both  <dig> and  <dig> hours.
other studies of epithelial lung cells in mice have shown significant up regulation of this gene in association with lung injury, though on much shorter time scales  <cit> .
up-regulation of egr <dig> and egr <dig> have been seen after wounding in mouse studies at several stages of development from embryo to adult, though knockout studies show that neither gene is essential to healing  <cit> .
this suggests a redundancy in systems in the cellular response to trauma.
such backup systems are excluded in this study by the selection criteria as a gene must appear in all three experimental sets to be selected.
the timescale for egr <dig> up-regulation in these cases is much faster and is reported to be insignificant  <dig> min post trauma.
similarly, egr <dig> was reported to decrease to near zero after  <dig> hour.
egr <dig> is a master transcription factor that has been shown to be up-regulated by histamine in human aortic endothelial cells  <cit> .
it is not known whether this effect also exists in pulmonary endothelial cells, but based on these data this seems to be a possibility.
it is curious, however, that this study finds egr <dig> to be strongly down regulated, in contrast to other studies.
the immediate early gene egr <dig> is also activated by injury, suggesting that mechanical stress of the cellular membrane and viral infection may have a common factor in the response triggered in the cell  <cit> .
there are also significant differences between an intense, onetime injury and the more gradual onset and constant stress of a viral infection.
these differences may help explain the faster timescales of gene activation associated with injury.
with respect to virus response, studies by djavani et al.
report down-regulation of egr <dig> and egr <dig> after infection with the lymphocytic choriomeningitis virus  in a monkey model  <cit> .
down-regulation of these genes has been recorded by djavani et al.
after day  <dig> until the end of their measurements at day  <dig>  this evidence is consistent with our findings.
thus it seems that virus infection triggers different reactions in the same first responder genes compared to wound healing.
interested to report with this respect is a regulatory network identified by djavani et al.
that includes egr <dig>  egr <dig>  fos, jun and ptgs <dig> .
in contrast to djavani et al., ptgs <dig> and il1rl <dig> are up-regulated .
these results indicate moderately different host responses during different viral infections even for such a compact and highly connected network of major host responding genes.
a study of cellular response in birds to h5n <dig>  <cit>  reports several genes to be significantly regulated.
none of the genes reported match the genes found in this study, though several are similar.
many genes, such as socs <dig>  il17c and stat <dig> in this study, are similar to the genes socs <dig>  il17a and stat <dig> reported in  <cit> .
these genes show opposite regulation in this study compared to the results in birds.
other genes, such as tlr <dig> in this study and tlr <dig> in birds are both found to be activated by exposure to h5n <dig>
of the strongly regulated genes, several are also found in the svm analysis described in the last portion of the methods section.
the genes common to the significance analysis and the top  <dig> components of the svm analysis are shown in table  <dig>  the two largest components of the vector describing the optimal hyperplane are for the genes cyr <dig> and socs <dig>  these genes have been associated with ventilator-induced lung injury in mice, along with ccl <dig>  <cit> .
it has also been found that androgen receptors enhance stat <dig>  which in turn regulates transcription of socs <dig>  <cit> .
this system is responsible for leptin regulation and may indicate a change in the energy use of a cell when responding to a pathogen.
variations in levels of cyr <dig> have also been reported in human tumor cell lines from nervous tissue along with a structurally related gene, ctgf  <cit> .
over-expression of zfp <dig> has been found after wounding keratinocytes in human tissue  <cit> , though this is in contrast to the down regulation observed in this study.
the study by  <cit>  also shows fos and egr <dig> to be activated by injury, again with opposite results of the data presented here where both are found to be down regulated.
up regulation of zfp <dig> has also been reported between bouts of muscular exercise  <cit> .
the reason for the down-regulation of zpf <dig> upon exposure to h5n <dig> while it is up regulated in response to physical injury is probably due to modulation effects caused by the virus infection.
svm results don't share any of the genes found by bingo analysis.
that is, no gene was found to be both associated with a significantly over represented go node and among the most relevant genes in the svm analysis.
rather, the genes found by svm tend to be functionally related to many of the genes found in significant go clusters.
these genes include jun, fos, fosb, egr <dig>  dusp <dig>  and cyr <dig>  this distinction is likely due to svm selecting based on differential expression and without regard to relative statistical significance or gene relationships.
curiously, the ccl <dig> gene that features as a prominent hub in the human network graph is not found to be significant in either the bingo or the svm analysis.
the synthesized networks enable us to determine the regulations  of the selected genes.
for example, saa   <dig> and  <dig> are important host markers for h5n <dig> hpai infection.
cxcl <dig>  cxcl  <dig> and  <dig>  cxcr <dig> along with il1a regulates expression of saa proteins that induce immune response molecules specific for h5n <dig> infection , but not rsv or mock infection.
figure  <dig> shows response networks at  <dig> h and  <dig> h after infection between differentially expressed genes of h5n <dig> and rsv .
already at  <dig> h, cxcl <dig> is  <dig>  times more expressed in h5n <dig> than in rsv.
this ratio increases to  <dig>  at  <dig> h. similar increases can be identified for cxcl <dig> and cxcl <dig>  the relative expression between h5n <dig> and rsv for these genes change from  <dig>  and  <dig>  at  <dig> h to  <dig>  and  <dig>  at  <dig> h, respectively.
with respect to oas genes, relative expression of oasl changes from  <dig>  to  <dig>  between  <dig> h and  <dig> h. interesting to note at  <dig> h is the icam <dig> triggered two-pronged expressed cascade to the fos/jun pair as well as to the chemokine ligand family  and their corresponding receptors .
thus, h5n <dig> seems to trigger a variety of cytokine response in contrast to rsv infections.
the exceptions are ccr <dig>  cxcl <dig> and ccl <dig>  these chemokines are suppressed by h5n <dig>  indicating a weakened anti-viral response induced by h5n <dig> infections.
the immune responses are further developed into viral specific immune responses by expressing molecules in interferon family.
targeting any of these genes aligned in immune response pathways can boost human anti-viral immune system.
CONCLUSIONS
the expression of approximately  <dig> genes in human epithelial lung cells is found to be significantly different at  <dig> and  <dig> hours after h5n <dig> exposure compared to normal cellular metabolism or to response to rsv infection.
only those genes found to be significant at  <dig> hours are significantly clustered in the gene ontology with cell cycle and various immune response nodes being over represented.
although many genes are found to be differentially expressed after exposure to rsv that are not found in either the control or in the h5n <dig> experiment, no significant clustering was found using the bingo analysis.
the faster time scales and more intense immunological response may be factors in the virulence of h5n <dig>  these results are consistent with reports from infections caused by other aggressive viruses, such as lcmv.
network responses of major gene products affected by virulent infection seems to be conserved between h5n <dig> and lcmv infections.
although detailed responses clearly distinguish between different viruses.
h5n <dig> causes host immune response by inducing large number of chemokines at the early stages  of infection.
however, cxcl <dig> and cxcl <dig> that are the keys to develop host anti-viral responses are suppressed.
balance among cxcl chemokines may be important to reduce the h5n <dig> mediated complications .
future studies looking at time scales from 12- <dig> hours would be helpful in addition to real-time pcr of the most significant genes found here to better determine their roles in the response to h5n <dig>
potential applications of these findings include;  the identification early host biomarkers that can be used to detect specifically h5n <dig> infection during the early stages when the clinical symptoms have not been developed,  the selection of host targets to develop therapeutic for h5n <dig> infection.

 techniques such as microarray analysis allow measurements of the differential gene expression in cells for tens of thousands of genes simultaneously. the ability to measure changes in the transcription activity of a cell in response to an external stimulus allows for a system-wide approach in which pathways and sub-networks are analyzed rather than the activity of isolated genes. further, the development of biological knowledge systems such as the gene ontology have provided a framework in which groups of genes can be classified in three areas: biological processes, molecular function and cellular components. this ontological classification scheme of gene function gives a hierarchical context in which groups of genes can be regarded to determine how closely they are functionally related. a complimentary approach to above classification based on go is the assessment of molecular functions in the context of known interactions between genes, dna/rnas, proteins and small chemicals, as mapped in biochemical interaction maps, pathways and networks. the novel combination of these biochemical networks, along with the classifications provided by the go, allows important clusters of genes in the cellular response to be identified. it further provides evidence by adjacency and pathway connectivity to assign genes that may not be significantly expressed to the relevant gene clusters. here, these methods are used to study properties of avian influenza infection with h5n virus, and to compare this infection to another upper respiratory tract infection, namely respiratory syncytial virus. the h5n influenza virus shows remarkably higher virulence than other strains of influenza. a greater understanding of the h5n virus is motivated by epidemiological concerns, particularly in-light of the recent emergence of the h1n strain, because it is a prime candidate as a future pandemic infection should it mutate or reassort into a form that can be easily contracted by humans. as a cross check on the significance analysis, a support vector machine algorithm is used to identify which genes show the greatest differences in their expressions between the h5n infected and control samples. this ranking is then compared to the significance analysis and genes associated with over represented go nodes as well as genes that are closely associated with significant genes through interactions in the human network. this cross check will allow us to identify nodes that are not properly annotated, thus are not captured by the go analysis.  results are presented in threefold. first, significant clustering of genes into sub-graphs of the gene ontology are identified using the go enrichment analysis plugin bingo for cytoscape. second, many of the most strongly up and down regulated genes are examined and their possible function in the cellular response of normal human bronchial epithelial cells to h5n is considered with comparison to rsv and mock infections. comparisons were made at and hours postinfection for comparison of gene expression changes prior to and following productive viral replication, generally 12- hours postinfection in this nhbe culture model. viral replication was verified by standard plaque assay techniques under the appropriate biocontainment levels. a total of and genes were found to be both significant biologically and statistically post infection at and hours, respectively. of these, only a small fraction are associated with over represented go nodes. third, human response networks are calculated and correlated with go. significant sub-graphs after and hours of h5n exposure, and significant genes relative to the controls were identified, respectively. in spite of genes being found at hours, no significant over-representation of any go nodes was found by bingo. at hours after infection, several go nodes showed over-representation and are listed in table along with the significant genes that are annotated with the corresponding go id. only nodes that are significant at the level using a bonferroni correction are listed. using the more liberal benjamini correction did not yield appreciably different graphs. the genes associated with each of these go nodes and their functional interactions with other genes as described by our constructed human network are shown in figure. most of the genes in the go clustering and those found associated/related in the human network are up-regulated, with a minority being down-regulated. many of the genes with the greatest change in expression, however, were down regulated such as egr fos and egr as shown in table. the most significant go nodes are given with their raw p-values. under each go entry is a list of the genes associated with that node. errors are based on the variation of the fold change in expression between the three independent trials. egr has the greatest average down-regulation of all genes observed in this study at both and hours with fos being more down-regulated than egr at hours and fos and egr switching places at hours. the log fold changes are shown. another visualization of these results is depicted in figure, which contains a network that used daughters of bingo nodes as seeds for the human response network. as a result there are many genes connected to each go node. the increased number of paths between go nodes obscures the genes that are at the hub of activity, though fos, ifi stat cxcl and cdc are rather well connected. this is in contrast to figure which shows a graph where the significant genes were used as seeds regardless of their go connections to generate a human response network, and the resulting graph was then merged with the go nodes found to be significant with bingo. interestingly, no significant over-representation of go nodes can be found among the significantly represented genes during rsv infection. that is, looking at the genes that are both biologically and statistically significant in the rsv but not in the mock assays. this may indicate that the response to rsv at times earlier than hours does not involve activating genes that are not part of the normal metabolic behavior of the cell. it is possible that there is a more subtle interplay between the gene activations in how the cell orchestrates a response. alternatively, the effects of early rsv infection could be small such that the cell has not mustered significant changes in gene expression by hours post infection. in any case, using the union of all genes found to be significant in any of the control experiments is rather conservative and may exclude sufficient true positives to make finding significantly over represented go nodes difficult; however, this also highlights the dramatic response of the cell to infection by h5n genes of interest although no significant go nodes are found at hours, there is one sub-network associated with binding in the gene ontology that contains a fair number of genes. at hours this sub-network contains a handful of genes including ctgf, cyr sdpr and lgals by hours this has expanded to accommodate numerous genes. this parent node common to the genes of this subnetwork is associated with ifit a gene that codes for an interferon induced protein. other subnetwork that are easily identified by visual inspection include genes involving transcription regulation, with the genes egr jun, mcm fosb, fos and zfp being significantly regulated at both and hours, and genes involved with post transcriptional/translational modification such as tap isg and plk there are also a number of kinase/phosphatase related genes, dusp abcc socs among these, several of these genes also appear among the top components to the vector normal to the ohp in the svm analysis. table lists genes from table that appear as significant in the and hour experiments. although most of these genes are not found in the bingo analysis, they are generally found to be highly connected to those genes through the human network. many of these genes, including cyr egr jun and dusp are prominently displayed in the response network in figure genes are listed in order of importance in the svm analysis. the fold change in each gene is the average fold change in gene expression including both the and hour data. in the last two columns, a "+" indicates that the gene was found in both the significance and svm analyses at or hours, respectively. a "-" indicates that the gene was not found in the results in both analyses at or hours. genes through sfrs are among the top and through the end of the list are in the top the components of the ohp in the svm analysis are displayed along with the average fold change of the gene in the h5n data and control data, and the average p-values in the h5n and control data. the length of each component is also given. a negative component to the vector normal to the ohp indicates a decrease in the fold change in gene expression from the control to the h5n exposures while a positive component indicates an increase in the differential expression from control to h5n among the three most dramatically regulated genes at both and hours is the early growth response gene egr which is down-regulated by about an order of magnitude at both and hours. other studies of epithelial lung cells in mice have shown significant up regulation of this gene in association with lung injury, though on much shorter time scales. up-regulation of egr and egr have been seen after wounding in mouse studies at several stages of development from embryo to adult, though knockout studies show that neither gene is essential to healing. this suggests a redundancy in systems in the cellular response to trauma. such backup systems are excluded in this study by the selection criteria as a gene must appear in all three experimental sets to be selected. the timescale for egr up-regulation in these cases is much faster and is reported to be insignificant min post trauma. similarly, egr was reported to decrease to near zero after hour. egr is a master transcription factor that has been shown to be up-regulated by histamine in human aortic endothelial cells. it is not known whether this effect also exists in pulmonary endothelial cells, but based on these data this seems to be a possibility. it is curious, however, that this study finds egr to be strongly down regulated, in contrast to other studies. the immediate early gene egr is also activated by injury, suggesting that mechanical stress of the cellular membrane and viral infection may have a common factor in the response triggered in the cell. there are also significant differences between an intense, onetime injury and the more gradual onset and constant stress of a viral infection. these differences may help explain the faster timescales of gene activation associated with injury. with respect to virus response, studies by djavani et al. report down-regulation of egr and egr after infection with the lymphocytic choriomeningitis virus in a monkey model. down-regulation of these genes has been recorded by djavani et al. after day until the end of their measurements at day this evidence is consistent with our findings. thus it seems that virus infection triggers different reactions in the same first responder genes compared to wound healing. interested to report with this respect is a regulatory network identified by djavani et al. that includes egr egr fos, jun and ptgs. in contrast to djavani et al., ptgs and il1rl are up-regulated. these results indicate moderately different host responses during different viral infections even for such a compact and highly connected network of major host responding genes. a study of cellular response in birds to h5n reports several genes to be significantly regulated. none of the genes reported match the genes found in this study, though several are similar. many genes, such as socs il17c and stat in this study, are similar to the genes socs il17a and stat reported in. these genes show opposite regulation in this study compared to the results in birds. other genes, such as tlr in this study and tlr in birds are both found to be activated by exposure to h5n of the strongly regulated genes, several are also found in the svm analysis described in the last portion of the methods section. the genes common to the significance analysis and the top components of the svm analysis are shown in table the two largest components of the vector describing the optimal hyperplane are for the genes cyr and socs these genes have been associated with ventilator-induced lung injury in mice, along with ccl. it has also been found that androgen receptors enhance stat which in turn regulates transcription of socs. this system is responsible for leptin regulation and may indicate a change in the energy use of a cell when responding to a pathogen. variations in levels of cyr have also been reported in human tumor cell lines from nervous tissue along with a structurally related gene, ctgf. over-expression of zfp has been found after wounding keratinocytes in human tissue, though this is in contrast to the down regulation observed in this study. the study by also shows fos and egr to be activated by injury, again with opposite results of the data presented here where both are found to be down regulated. up regulation of zfp has also been reported between bouts of muscular exercise. the reason for the down-regulation of zpf upon exposure to h5n while it is up regulated in response to physical injury is probably due to modulation effects caused by the virus infection. svm results don't share any of the genes found by bingo analysis. that is, no gene was found to be both associated with a significantly over represented go node and among the most relevant genes in the svm analysis. rather, the genes found by svm tend to be functionally related to many of the genes found in significant go clusters. these genes include jun, fos, fosb, egr dusp and cyr this distinction is likely due to svm selecting based on differential expression and without regard to relative statistical significance or gene relationships. curiously, the ccl gene that features as a prominent hub in the human network graph is not found to be significant in either the bingo or the svm analysis. the synthesized networks enable us to determine the regulations of the selected genes. for example, saa and are important host markers for h5n hpai infection. cxcl cxcl and cxcr along with il1a regulates expression of saa proteins that induce immune response molecules specific for h5n infection, but not rsv or mock infection. figure shows response networks at h and h after infection between differentially expressed genes of h5n and rsv. already at h, cxcl is times more expressed in h5n than in rsv. this ratio increases to at h. similar increases can be identified for cxcl and cxcl the relative expression between h5n and rsv for these genes change from and at h to and at h, respectively. with respect to oas genes, relative expression of oasl changes from to between h and h. interesting to note at h is the icam triggered two-pronged expressed cascade to the fos/jun pair as well as to the chemokine ligand family and their corresponding receptors. thus, h5n seems to trigger a variety of cytokine response in contrast to rsv infections. the exceptions are ccr cxcl and ccl these chemokines are suppressed by h5n indicating a weakened anti-viral response induced by h5n infections. the immune responses are further developed into viral specific immune responses by expressing molecules in interferon family. targeting any of these genes aligned in immune response pathways can boost human anti-viral immune system.  the expression of approximately genes in human epithelial lung cells is found to be significantly different at and hours after h5n exposure compared to normal cellular metabolism or to response to rsv infection. only those genes found to be significant at hours are significantly clustered in the gene ontology with cell cycle and various immune response nodes being over represented. although many genes are found to be differentially expressed after exposure to rsv that are not found in either the control or in the h5n experiment, no significant clustering was found using the bingo analysis. the faster time scales and more intense immunological response may be factors in the virulence of h5n these results are consistent with reports from infections caused by other aggressive viruses, such as lcmv. network responses of major gene products affected by virulent infection seems to be conserved between h5n and lcmv infections. although detailed responses clearly distinguish between different viruses. h5n causes host immune response by inducing large number of chemokines at the early stages of infection. however, cxcl and cxcl that are the keys to develop host anti-viral responses are suppressed. balance among cxcl chemokines may be important to reduce the h5n mediated complications. future studies looking at time scales from 12- hours would be helpful in addition to real-time pcr of the most significant genes found here to better determine their roles in the response to h5n potential applications of these findings include; the identification early host biomarkers that can be used to detect specifically h5n infection during the early stages when the clinical symptoms have not been developed, the selection of host targets to develop therapeutic for h5n infection. 
these gene expression data are then used as seeds to find important nodes by using a novel combination of the gene ontology database and the human network of gene interactions. analysis of gene clustering in the gene ontology shows no significant clustering of genes unique to h5n response at hours post infection. there were no significant clusters of genes in the gene ontology for the control or rsv experiments that were unique relative to the h5n response. many of the genes that are found to be significantly expressed in h5n response relative to the control experiments are not found to cluster significantly in the gene ontology. these genes are, however, often closely linked to the clustered genes through the human network. we analyzed differential gene expression of lung epithelial cells to compare the response to h5n infection with a more benign infection with respiratory syncytial virus. the recent emergence of the h5n influenza virus from avian reservoirs has raised concern about future influenza strains of high virulence emerging that could easily infect humans.
 the recent emergence of the h5n influenza virus from avian reservoirs has raised concern about future influenza strains of high virulence emerging that could easily infect humans. we analyzed differential gene expression of lung epithelial cells to compare the response to h5n infection with a more benign infection with respiratory syncytial virus. these gene expression data are then used as seeds to find important nodes by using a novel combination of the gene ontology database and the human network of gene interactions. additional analysis of the data is conducted by training support vector machines with the data and examining the orientations of the optimal hyperplanes generated.  analysis of gene clustering in the gene ontology shows no significant clustering of genes unique to h5n response at hours post infection. at hours post infection, however, a number of significant gene clusters are found for nodes representing "immune response" and "response to virus" terms. there were no significant clusters of genes in the gene ontology for the control or rsv experiments that were unique relative to the h5n response. the genes found to be most important in distinguishing h5n infected cells from the controls using svm showed a large degree of overlap with the list of significantly regulated genes. however, though none of these genes were members of the go clusters found to be significant.  characteristics of h5n infection compared to rsv infection show several immune response factors that are specific for each of these infections. these include faster timescales within the cell as well as a more focused activation of immunity factors. many of the genes that are found to be significantly expressed in h5n response relative to the control experiments are not found to cluster significantly in the gene ontology. these genes are, however, often closely linked to the clustered genes through the human network. this may suggest the need for more diverse annotations of these genes and verification of their action in immune response. 