{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,4]],"date-time":"2026-10-04T17:19:22Z","timestamp":1791134362897,"version":"4.1.0"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2004,8,16]],"date-time":"2004-08-16T00:00:00Z","timestamp":1092614400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/2.0"},{"start":{"date-parts":[[2004,8,16]],"date-time":"2004-08-16T00:00:00Z","timestamp":1092614400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/2.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                        <jats:title>Background<\/jats:title>\n                        <jats:p>A necessary step for a genome level analysis of the cellular metabolism is the <jats:italic>in silico<\/jats:italic> reconstruction of the metabolic network from genome sequences. The available methods are mainly based on the annotation of genome sequences including two successive steps, the prediction of coding sequences (CDS) and their function assignment. The annotation process takes time. The available methods often encounter difficulties when dealing with unfinished error-containing genomic sequence.<\/jats:p>\n                     <\/jats:sec><jats:sec>\n                        <jats:title>Results<\/jats:title>\n                        <jats:p>In this work a fast method is proposed to use unannotated genome sequence for predicting CDSs and for an <jats:italic>in silico<\/jats:italic> reconstruction of metabolic networks. Instead of using predicted genes or CDSs to query public databases, entries from public DNA or protein databases are used as queries to search a local database of the unannotated genome sequence to predict CDSs. Functions are assigned to the predicted CDSs simultaneously. The well-annotated genome of <jats:italic>Salmonella typhimurium<\/jats:italic> LT2 is used as an example to demonstrate the applicability of the method. 97.7% of the CDSs in the original annotation are correctly identified. The use of SWISS-PROT-TrEMBL databases resulted in an identification of 98.9% of CDSs that have EC-numbers in the published annotation. Furthermore, two versions of sequences of the bacterium <jats:italic>Klebsiella pneumoniae<\/jats:italic> with different genome coverage (3.9 and 7.9 fold, respectively) are examined. The results suggest that a 3.9-fold coverage of the bacterial genome could be sufficiently used for the <jats:italic>in silico<\/jats:italic> reconstruction of the metabolic network. Compared to other gene finding methods such as CRITICA our method is more suitable for exploiting sequences of low genome coverage. Based on the new method, a program called IdentiCS (<jats:underline>Identi<\/jats:underline> fication of <jats:underline>C<\/jats:underline> oding <jats:underline>S<\/jats:underline> equences from Unfinished Genome Sequences) is delivered that combines the identification of CDSs with the reconstruction, comparison and visualization of metabolic networks (free to download at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"http:\/\/genome.gbf.de\/bioinformatics\/index.html\">http:\/\/genome.gbf.de\/bioinformatics\/index.html<\/jats:ext-link>).<\/jats:p>\n                     <\/jats:sec><jats:sec>\n                        <jats:title>Conclusions<\/jats:title>\n                        <jats:p>The reversed querying process and the program IdentiCS allow a fast and adequate prediction protein coding sequences and reconstruction of the potential metabolic network from low coverage genome sequences of bacteria. The new method can accelerate the use of genomic data for studying cellular metabolism.<\/jats:p>\n                     <\/jats:sec>","DOI":"10.1186\/1471-2105-5-112","type":"journal-article","created":{"date-parts":[[2004,8,20]],"date-time":"2004-08-20T06:22:51Z","timestamp":1092982971000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["IdentiCS \u2013 Identification of coding sequence and in silico reconstruction of the metabolic network directly from unannotated low-coverage bacterial genome sequence"],"prefix":"10.1186","volume":"5","author":[{"given":"Jibin","family":"Sun","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"An-Ping","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2004,8,16]]},"reference":[{"key":"228_CR1","doi-asserted-by":"publisher","first-page":"270","DOI":"10.1093\/bioinformatics\/19.2.270","volume":"19","author":"HW Ma","year":"2003","unstructured":"Ma HW, Zeng AP: Reconstruction of metabolic networks from genome data and analysis of their global structure for various organisms.\n                           Bioinformatics 2003, 19: 270\u2013277. 10.1093\/bioinformatics\/19.2.270","journal-title":"Bioinformatics"},{"key":"228_CR2","doi-asserted-by":"publisher","first-page":"1423","DOI":"10.1093\/bioinformatics\/btg177","volume":"19","author":"HW Ma","year":"2003","unstructured":"Ma HW, Zeng AP: The connectivity structure, giant strong component and centrality of metabolic networks.\n                           Bioinformatics 2003, 19: 1423\u20131430. 10.1093\/bioinformatics\/btg177","journal-title":"Bioinformatics"},{"key":"228_CR3","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1093\/nar\/28.1.123","volume":"28","author":"R Overbeek","year":"2000","unstructured":"Overbeek R, Larsen N, Pusch GD, D'Souza M, Selkov E Jr, Kyrpides N, Fonstein M, Maltsev N, Selkov E: WIT: integrated system for high-throughput genome sequence analysis and metabolic reconstruction.\n                           Nucleic Acids Res 2000, 28: 123\u2013125. 10.1093\/nar\/28.1.123","journal-title":"Nucleic Acids Res"},{"key":"228_CR4","doi-asserted-by":"publisher","first-page":"929","DOI":"10.1126\/science.292.5518.929","volume":"292","author":"T Ideker","year":"2001","unstructured":"Ideker T, Thorsson V, Ranish JA, Christmas R, Buhler J, Eng JK, Bumgarner R, Goodlett DR, Aebersold R, Hood L: Integrated genomic and proteomic analyses of a systematically perturbed metabolic network.\n                           Science 2001, 292: 929\u2013934. 10.1126\/science.292.5518.929","journal-title":"Science"},{"key":"228_CR5","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1093\/nar\/28.1.27","volume":"28","author":"M Kanehisa","year":"2000","unstructured":"Kanehisa M, Goto S: KEGG: kyoto encyclopedia of genes and genomes.\n                           Nucleic Acids Res 2000, 28: 27\u201330. 10.1093\/nar\/28.1.27","journal-title":"Nucleic Acids Res"},{"key":"228_CR6","volume-title":"Biochemical Pathways","author":"G Michal","year":"1992","unstructured":"Michal G: Biochemical Pathways\n                           3 Edition Boehringer Mannheim, Germany 1992.","edition":"3"},{"key":"228_CR7","volume-title":"Biochemical Pathways","author":"G Michal","year":"1999","unstructured":"Michal G: Biochemical Pathways Heidelberg; 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