traditionally , most rna molecules were regarded as carriers conveying information from the gene to the translation machinery .
the most prominent exceptions to this are transfer rna ( trna ) and ribosomal rna ( rrna ) , both of which are directly involved in the process of translation . however , since the late 1990s , it has been widely acknowledged that other types of non - protein - coding rna molecules are present in organisms ranging from bacteria to mammals , which affect a large variety of processes including plasmid replication , phage development , bacterial virulence , chromosome structure , dna transcription , rna processing and modification , development control and others ( 116 ) .
these observations suggest that the traditional view of the structure of the genetic regulatory systems in organisms is far from complete
. therefore , further research on non - protein - coding rna will give us a new framework for considering and understanding the genomic programming of biological complexity .
however , the unsystematic naming of non - protein - coding rnas may be an impediment to effective research . the term small rnas ( srnas ) has been predominantly used for such rnas in bacteria , whereas the term non - coding rnas ( ncrnas ) has been the most common term for eukaryotic rnas of this kind ( 17,18 ) . to have a common term for all such rnas ,
we have opted to apply the term ncrna to all these functional rnas , irrespective of the realm of life in which they might appear .
the understanding of the importance of ncrnas in basic cellular processes is ever increasing , and new members and classes of ncrnas are continuously being reported .
thus , over the years , several databases have been established to collect , organize and classify ncrna sequences and information .
some databases are intended to collect only certain category of ncrnas , such as srp rnas , tmrnas or rnase p rnas , whereas others , such as the small rna database , the non - coding rna database and the rfam database , have collected ncrnas of several categories ( 1924 ) . however , even in the latter kind of databases certain ncrna members or classes are missing .
another problem with all the current databases is that the classification systems for ncrnas used nowadays are not uniform and only a few attempts have been made to integrate the various classification systems . in these classification systems , some ncrna groups are named according to cellular localizations , such as snrnas , snornas or scrnas , some are named according to functions , like prnas ( package rnas ) , grnas ( guide rnas ) or tmrnas ( transfer - messenger rnas ) , and others again are simply labeled according to their sedimentation coefficients ( 6s rna , 5.3s rna , etc . ) .
furthermore , because of this lack of integration , one type of ncrna often appears under several names or in more than one category ( 7,12,2530 ) .
noncode comprises almost all ncrnas now publicly available ( except trnas and rrnas ) that are either confirmed experimentally or predicted computationally .
the first release of noncode ( v1.0 ) contains 5339 non - redundant sequences from 861 organisms , including eukaryotes , eubacteria , archaebacteria , virus and viroids .
furthermore , to integrate existing classification systems , a new classification system labeled the process function class ( pfclass ) has been introduced , based on the cellular process and function in which a given ncrna is involved . pfclass provides a unified classification system and a concise functional annotation of ncrnas . according to the cellular process involved ,
the pfclass classification system is the first attempt of a unified classification system for ncrnas .
it is our hope that this integrated system will help in clearing up the classification problem . in conclusion ,
the aim of the noncode database is to be a unified gateway to search , retrieve and update information about ncrnas in order to facilitate research on ncrnas , gene networks and functional genomics . through a user - friendly web interface at http://noncode.bioinfo.org.cn ,
genbank entries were the major source of data , and the pubmed database was used as the starting point for the data collection ( 31 ) .
the publications that matched with these queries were then examined and the ncrna sequences were extracted from the obtained literature . by reading the filtered literature , a new set of ncrna keywords were gained and added into the keywords table .
this new keywords table was used to filter the genbank bct , inv , mam , phg , pln , pri , rod , vrl and vrt divisions automatically , and the filtered result was then manually confirmed .
all the data are integrated and organized in such a manner that users can efficiently query and browse information .
one significant characteristic of noncode is its content of additional information on the ncrnas obtained from the related literature .
( i ) for each sequence filtered from genbank , we manually checked whether or not it represented an actual ncrna and assigned the confirmed sequence an accession number ( ncid , i.e. ncrna i d ) .
( ii ) basic information  name , alias , length , organisms , references , etc.of confirmed sequences was collected from genbank .
( iii ) additional information concerning function , cellular role , cellular location , etc .
each ncrna has also been annotated with one of the five specific mechanisms ( sequence base pairing , structural complementarity , spatial blocking , catalysis or epimodification ) , through which it exerts its function .
( iv ) according to our pfclass classification system , one or more of the 26 pfclasses were assigned to all ncrnas . moreover ,
a subset of 1114 ncrnas have been divided into nine additional categories according to whether they are specific to gender or tissue or associated with tumors and diseases , etc .
( v ) to visualize the location of an ncrna in the genome or in a specific dna fragment , along with regulatory elements in the flanking sequences , genbank annotations were used to create figures for all ncrnas .
( vi ) each ncrna sequence was checked for redundancies using perl scripts , and each cluster of redundant sequences was given a non - redundant accession number ( uniqid , i.e. unique ncrna i d ) .
( vii ) the secondary structures of non - redundant ncrna sequences were predicted using the vienna rna package ( 32 ) .
ever since the beginning of ncrna research there has not been in place any integrated system for classification , and therefore , exists a considerable measure of confusion with respect to naming of ncrnas .
therefore , when the noncode database was established it was carefully considered as how to establish classification criteria that might increase the usefulness of the database resource .
the cellular process and function of an ncrna was chosen as the basic criterion for a unified classification system called pfclass in noncode . when labeled according to this system , each kind of ncrna is named after its cellular process and corresponding function .
the actual category is given according to two or three levels of keywords connected by an underscore .
the first keyword will be dna , rna or protein , representing a cellular process in which either of the three molecular types is a crucial component .
the second keyword describes the actual process , and if the ncrna is involved in a complex process with several aspects , a third keyword may further indicate a more specific function of the ncrna .
for example , the snrna u1 will be assigned to the pfclass rna_processing_splicing , and rnase p rnas to the pfclass rna_processing_cleavage ( for details see table 1 ) .
the pfclass classification system represents the first attempt of a unified classification system for ncrnas . in the future , as our understanding of ncrnas
deepen , and the content of noncode further expands , steps will be taken to further extend and perfect the pfclass system in order to increase its usefulness . to further harmonize the exchange of data between different systems , application of gene ontology ( go ) ( 33 ) annotation on our pfclass system will be considered .
genbank entries were the major source of data , and the pubmed database was used as the starting point for the data collection ( 31 ) .
the publications that matched with these queries were then examined and the ncrna sequences were extracted from the obtained literature . by reading the filtered literature , a new set of ncrna keywords were gained and added into the keywords table .
this new keywords table was used to filter the genbank bct , inv , mam , phg , pln , pri , rod , vrl and vrt divisions automatically , and the filtered result was then manually confirmed .
all the data are integrated and organized in such a manner that users can efficiently query and browse information .
one significant characteristic of noncode is its content of additional information on the ncrnas obtained from the related literature . briefly , seven steps were carried out after the genbank screening .
( i ) for each sequence filtered from genbank , we manually checked whether or not it represented an actual ncrna and assigned the confirmed sequence an accession number ( ncid , i.e. ncrna i d ) .
( ii ) basic information  name , alias , length , organisms , references , etc.of confirmed sequences was collected from genbank .
( iii ) additional information concerning function , cellular role , cellular location , etc .
each ncrna has also been annotated with one of the five specific mechanisms ( sequence base pairing , structural complementarity , spatial blocking , catalysis or epimodification ) , through which it exerts its function .
( iv ) according to our pfclass classification system , one or more of the 26 pfclasses were assigned to all ncrnas . moreover ,
a subset of 1114 ncrnas have been divided into nine additional categories according to whether they are specific to gender or tissue or associated with tumors and diseases , etc .
( v ) to visualize the location of an ncrna in the genome or in a specific dna fragment , along with regulatory elements in the flanking sequences , genbank annotations were used to create figures for all ncrnas .
( vi ) each ncrna sequence was checked for redundancies using perl scripts , and each cluster of redundant sequences was given a non - redundant accession number ( uniqid , i.e. unique ncrna i d ) .
( vii ) the secondary structures of non - redundant ncrna sequences were predicted using the vienna rna package ( 32 ) .
ever since the beginning of ncrna research there has not been in place any integrated system for classification , and therefore , exists a considerable measure of confusion with respect to naming of ncrnas .
therefore , when the noncode database was established it was carefully considered as how to establish classification criteria that might increase the usefulness of the database resource .
the cellular process and function of an ncrna was chosen as the basic criterion for a unified classification system called pfclass in noncode . when labeled according to this system , each kind of ncrna is named after its cellular process and corresponding function .
the actual category is given according to two or three levels of keywords connected by an underscore .
the first keyword will be dna , rna or protein , representing a cellular process in which either of the three molecular types is a crucial component .
the second keyword describes the actual process , and if the ncrna is involved in a complex process with several aspects , a third keyword may further indicate a more specific function of the ncrna .
for example , the snrna u1 will be assigned to the pfclass rna_processing_splicing , and rnase p rnas to the pfclass rna_processing_cleavage ( for details see table 1 ) .
the pfclass classification system represents the first attempt of a unified classification system for ncrnas . in the future , as our understanding of ncrnas
deepen , and the content of noncode further expands , steps will be taken to further extend and perfect the pfclass system in order to increase its usefulness . to further harmonize the exchange of data between different systems , application of gene ontology ( go ) ( 33 ) annotation on our pfclass system will be considered .
till date , more than 10  000 sequences filtered from genbank by our in - house program have been manually examined .
the current release ( v.1.0 ) of noncode contains a total of 6232 entries assigned to 26 pfclasses , and covers 109 traditional classes such as snrna , snorna , microrna and rnase p rna .
basic information on each entry is provided , including accession number in genbank , traditional class , name , pfclass , organism , reference , uniqid ( accession number without redundancy in noncode ) and ncid ( accession number with redundancy in noncode ) , all of which can be used as keywords for data search .
noncode also provides additional information on function and cellular role , cellular location , chromosomal information , alternative names , secondary structure and whether or not the ncrna has undergone splicing .
each ncrna has also been annotated with one of the five specific mechanisms ( sequence base pairing , structural complementarity , spatial blocking , catalysis or epimodification ) , through which it exerts its function .
figures showing genomic locations for all ncrnas and their regulatory elements have been included , and a subdivision into nine additional classes ( outside the pfclass system ) has also been applied to a number of ncrnas .
noncode also offers an efficient search option , allowing recovery of sequence , related publications and other information . in the near future
( i ) for a number of ncrnas , information on function , location , etc
. is still lacking , and this information will be completed as soon as it becomes available .
( ii ) as the information on ncrnas increases and the content of noncode further expands , the pfclass system will be further extended and perfected in order to increase its usefulness .
go annotation on the pfclass system will also be considered seriously , with the aim of harmonized exchange of data between the different systems .
( iii ) additional services such as blast alignment , ncrnas prediction and possibilities for submission and registration of users ' sequences will be provided .
in addition , two large - scale screens for novel ncrnas in caenorhabditis elegans and human tissues are being carried out in our laboratory ( y. wang , z.y .
he , unpublished data ) , and the results will be added in the next version of noncode .
noncode is thus designed to adapt and to reflect the most current information on ncrnas available .
it will continue to grow in both content and functionality , and will be updated every six months to include any new data from literature and genbank .
we are indebted to all of our colleagues who focus much of their research efforts on the analyses of ncrnas .
kscx2 - 2 - 27 , national sciences foundation of china grant nos 39890070 and 60496320 , the national high technology development program of china under grant no .
2002aa231031 , national key basic research & development program 973 under grant nos 2002cb713805 and 2003cb715900 , and beijing science and technology commission grant no . h010210010113 .
 noncode is an integrated knowledge database dedicated to non - coding rnas ( ncrnas ) , that is to say , rnas that function without being translated into proteins . 
 all ncrnas in noncode were filtered automatically from literature and genbank , and were later manually curated . 
 the distinctive features of noncode are as follows : ( i ) the ncrnas in noncode include almost all the types of ncrnas , except transfer rnas and ribosomal rnas . 
 ( ii ) all ncrna sequences and their related information ( e.g. function , cellular role , cellular location , chromosomal information , etc . ) in noncode have been confirmed manually by consulting relevant literature : more than 80% of the entries are based on experimental data . 
 ( iii ) based on the cellular process and function , which a given ncrna is involved in , we introduced a novel classification system , labeled process function class , to integrate existing classification systems . 
 ( iv ) in addition , some 1100 ncrnas have been grouped into nine other classes according to whether they are specific to gender or tissue or associated with tumors and diseases , etc . 
 ( v ) noncode provides a user - friendly interface , a visualization platform and a convenient search option , allowing efficient recovery of sequence , regulatory elements in the flanking sequences , secondary structure , related publications and other information . 
 the first release of noncode ( v1.0 ) contains 5339 non - redundant sequences from 861 organisms , including eukaryotes , eubacteria , archaebacteria , virus and viroids . 
 access is free for all users through a web interface at http://noncode.bioinfo.org.cn . 
INTRODUCTION
METHODS AND IMPLEMENTATION
NONCODE pipeline
NONCODE annotation
NONCODE process function classification
CURRENT STATUS AND FUTURE DEVELOPMENTS
ACKNOWLEDGEMENTS