OM-FBA: Integrate Transcriptomics Data with Flux Balance Analysis to Decipher the Cell Metabolism Article Swipe
Weihua Guo
,
Xueyang Feng
·
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pone.0154188
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pone.0154188
Constraint-based metabolic modeling such as flux balance analysis (FBA) has been widely used to simulate cell metabolism. Thanks to its simplicity and flexibility, numerous algorithms have been developed based on FBA and successfully predicted the phenotypes of various biological systems. However, their phenotype predictions may not always be accurate in FBA because of using the objective function that is assumed for cell metabolism. To overcome this challenge, we have developed a novel computational framework, namely omFBA, to integrate multi-omics data (e.g. transcriptomics) into FBA to obtain omics-guided objective functions with high accuracy. In general, we first collected transcriptomics data and phenotype data from published database (e.g. GEO database) for different microorganisms such as Saccharomyces cerevisiae. We then developed a "Phenotype Match" algorithm to derive an objective function for FBA that could lead to the most accurate estimation of the known phenotype (e.g. ethanol yield). The derived objective function was next correlated with the transcriptomics data via regression analysis to generate the omics-guided objective function, which was next used to accurately simulate cell metabolism at unknown conditions. We have applied omFBA in studying sugar metabolism of S. cerevisiae and found that the ethanol yield could be accurately predicted in most of the cases tested (>80%) by using transcriptomics data alone, and revealed valuable metabolic insights such as the dynamics of flux ratios. Overall, omFBA presents a novel platform to potentially integrate multi-omics data simultaneously and could be incorporated with other FBA-derived tools by replacing the arbitrary objective function with the omics-guided objective functions.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1371/journal.pone.0154188
- https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0154188&type=printable
- OA Status
- gold
- Cited By
- 25
- References
- 60
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2337188110
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2337188110Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1371/journal.pone.0154188Digital Object Identifier
- Title
-
OM-FBA: Integrate Transcriptomics Data with Flux Balance Analysis to Decipher the Cell MetabolismWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2016Year of publication
- Publication date
-
2016-04-21Full publication date if available
- Authors
-
Weihua Guo, Xueyang FengList of authors in order
- Landing page
-
https://doi.org/10.1371/journal.pone.0154188Publisher landing page
- PDF URL
-
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0154188&type=printableDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0154188&type=printableDirect OA link when available
- Concepts
-
Flux balance analysis, Omics, Computational biology, Transcriptome, Metabolic flux analysis, Function (biology), Phenotype, Computer science, Metabolomics, Cell metabolism, Systems biology, Biology, Bioinformatics, Data mining, Metabolism, Cell, Genetics, Biochemistry, Gene, Gene expressionTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
25Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 5, 2023: 1, 2022: 3, 2021: 2Per-year citation counts (last 5 years)
- References (count)
-
60Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2337188110 |
|---|---|
| doi | https://doi.org/10.1371/journal.pone.0154188 |
| ids.doi | https://doi.org/10.1371/journal.pone.0154188 |
| ids.mag | 2337188110 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/27100883 |
| ids.openalex | https://openalex.org/W2337188110 |
| fwci | 1.73326165 |
| mesh[0].qualifier_ui | |
| mesh[0].descriptor_ui | D000465 |
| mesh[0].is_major_topic | True |
| mesh[0].qualifier_name | |
| mesh[0].descriptor_name | Algorithms |
| mesh[1].qualifier_ui | Q000235 |
| mesh[1].descriptor_ui | D004734 |
| mesh[1].is_major_topic | False |
| mesh[1].qualifier_name | genetics |
| mesh[1].descriptor_name | Energy Metabolism |
| mesh[2].qualifier_ui | Q000378 |
| mesh[2].descriptor_ui | D005690 |
| mesh[2].is_major_topic | False |
| mesh[2].qualifier_name | metabolism |
| mesh[2].descriptor_name | Galactose |
| mesh[3].qualifier_ui | Q000379 |
| mesh[3].descriptor_ui | D020869 |
| mesh[3].is_major_topic | False |
| mesh[3].qualifier_name | methods |
| mesh[3].descriptor_name | Gene Expression Profiling |
| mesh[4].qualifier_ui | Q000706 |
| mesh[4].descriptor_ui | D020869 |
| mesh[4].is_major_topic | False |
| mesh[4].qualifier_name | statistics & numerical data |
| mesh[4].descriptor_name | Gene Expression Profiling |
| mesh[5].qualifier_ui | |
| mesh[5].descriptor_ui | D053263 |
| mesh[5].is_major_topic | False |
| mesh[5].qualifier_name | |
| mesh[5].descriptor_name | Gene Regulatory Networks |
| mesh[6].qualifier_ui | |
| mesh[6].descriptor_ui | D005838 |
| mesh[6].is_major_topic | False |
| mesh[6].qualifier_name | |
| mesh[6].descriptor_name | Genotype |
| mesh[7].qualifier_ui | Q000378 |
| mesh[7].descriptor_ui | D005947 |
| mesh[7].is_major_topic | False |
| mesh[7].qualifier_name | metabolism |
| mesh[7].descriptor_name | Glucose |
| mesh[8].qualifier_ui | Q000379 |
| mesh[8].descriptor_ui | D055432 |
| mesh[8].is_major_topic | False |
| mesh[8].qualifier_name | methods |
| mesh[8].descriptor_name | Metabolomics |
| mesh[9].qualifier_ui | |
| mesh[9].descriptor_ui | D008957 |
| mesh[9].is_major_topic | True |
| mesh[9].qualifier_name | |
| mesh[9].descriptor_name | Models, Genetic |
| mesh[10].qualifier_ui | |
| mesh[10].descriptor_ui | D010641 |
| mesh[10].is_major_topic | False |
| mesh[10].qualifier_name | |
| mesh[10].descriptor_name | Phenotype |
| mesh[11].qualifier_ui | Q000379 |
| mesh[11].descriptor_ui | D040901 |
| mesh[11].is_major_topic | False |
| mesh[11].qualifier_name | methods |
| mesh[11].descriptor_name | Proteomics |
| mesh[12].qualifier_ui | |
| mesh[12].descriptor_ui | D015203 |
| mesh[12].is_major_topic | False |
| mesh[12].qualifier_name | |
| mesh[12].descriptor_name | Reproducibility of Results |
| mesh[13].qualifier_ui | Q000235 |
| mesh[13].descriptor_ui | D012441 |
| mesh[13].is_major_topic | False |
| mesh[13].qualifier_name | genetics |
| mesh[13].descriptor_name | Saccharomyces cerevisiae |
| mesh[14].qualifier_ui | Q000254 |
| mesh[14].descriptor_ui | D012441 |
| mesh[14].is_major_topic | False |
| mesh[14].qualifier_name | growth & development |
| mesh[14].descriptor_name | Saccharomyces cerevisiae |
| mesh[15].qualifier_ui | Q000378 |
| mesh[15].descriptor_ui | D012441 |
| mesh[15].is_major_topic | False |
| mesh[15].qualifier_name | metabolism |
| mesh[15].descriptor_name | Saccharomyces cerevisiae |
| mesh[16].qualifier_ui | Q000379 |
| mesh[16].descriptor_ui | D049490 |
| mesh[16].is_major_topic | False |
| mesh[16].qualifier_name | methods |
| mesh[16].descriptor_name | Systems Biology |
| mesh[17].qualifier_ui | |
| mesh[17].descriptor_ui | D000465 |
| mesh[17].is_major_topic | True |
| mesh[17].qualifier_name | |
| mesh[17].descriptor_name | Algorithms |
| mesh[18].qualifier_ui | Q000235 |
| mesh[18].descriptor_ui | D004734 |
| mesh[18].is_major_topic | False |
| mesh[18].qualifier_name | genetics |
| mesh[18].descriptor_name | Energy Metabolism |
| mesh[19].qualifier_ui | Q000378 |
| mesh[19].descriptor_ui | D005690 |
| mesh[19].is_major_topic | False |
| mesh[19].qualifier_name | metabolism |
| mesh[19].descriptor_name | Galactose |
| mesh[20].qualifier_ui | Q000379 |
| mesh[20].descriptor_ui | D020869 |
| mesh[20].is_major_topic | False |
| mesh[20].qualifier_name | methods |
| mesh[20].descriptor_name | Gene Expression Profiling |
| mesh[21].qualifier_ui | Q000706 |
| mesh[21].descriptor_ui | D020869 |
| mesh[21].is_major_topic | False |
| mesh[21].qualifier_name | statistics & numerical data |
| mesh[21].descriptor_name | Gene Expression Profiling |
| mesh[22].qualifier_ui | |
| mesh[22].descriptor_ui | D053263 |
| mesh[22].is_major_topic | False |
| mesh[22].qualifier_name | |
| mesh[22].descriptor_name | Gene Regulatory Networks |
| mesh[23].qualifier_ui | |
| mesh[23].descriptor_ui | D005838 |
| mesh[23].is_major_topic | False |
| mesh[23].qualifier_name | |
| mesh[23].descriptor_name | Genotype |
| mesh[24].qualifier_ui | Q000378 |
| mesh[24].descriptor_ui | D005947 |
| mesh[24].is_major_topic | False |
| mesh[24].qualifier_name | metabolism |
| mesh[24].descriptor_name | Glucose |
| mesh[25].qualifier_ui | Q000379 |
| mesh[25].descriptor_ui | D055432 |
| mesh[25].is_major_topic | False |
| mesh[25].qualifier_name | methods |
| mesh[25].descriptor_name | Metabolomics |
| mesh[26].qualifier_ui | |
| mesh[26].descriptor_ui | D008957 |
| mesh[26].is_major_topic | True |
| mesh[26].qualifier_name | |
| mesh[26].descriptor_name | Models, Genetic |
| mesh[27].qualifier_ui | |
| mesh[27].descriptor_ui | D010641 |
| mesh[27].is_major_topic | False |
| mesh[27].qualifier_name | |
| mesh[27].descriptor_name | Phenotype |
| mesh[28].qualifier_ui | Q000379 |
| mesh[28].descriptor_ui | D040901 |
| mesh[28].is_major_topic | False |
| mesh[28].qualifier_name | methods |
| mesh[28].descriptor_name | Proteomics |
| mesh[29].qualifier_ui | |
| mesh[29].descriptor_ui | D015203 |
| mesh[29].is_major_topic | False |
| mesh[29].qualifier_name | |
| mesh[29].descriptor_name | Reproducibility of Results |
| mesh[30].qualifier_ui | Q000235 |
| mesh[30].descriptor_ui | D012441 |
| mesh[30].is_major_topic | False |
| mesh[30].qualifier_name | genetics |
| mesh[30].descriptor_name | Saccharomyces cerevisiae |
| mesh[31].qualifier_ui | Q000254 |
| mesh[31].descriptor_ui | D012441 |
| mesh[31].is_major_topic | False |
| mesh[31].qualifier_name | growth & development |
| mesh[31].descriptor_name | Saccharomyces cerevisiae |
| mesh[32].qualifier_ui | Q000378 |
| mesh[32].descriptor_ui | D012441 |
| mesh[32].is_major_topic | False |
| mesh[32].qualifier_name | metabolism |
| mesh[32].descriptor_name | Saccharomyces cerevisiae |
| mesh[33].qualifier_ui | Q000379 |
| mesh[33].descriptor_ui | D049490 |
| mesh[33].is_major_topic | False |
| mesh[33].qualifier_name | methods |
| mesh[33].descriptor_name | Systems Biology |
| type | article |
| title | OM-FBA: Integrate Transcriptomics Data with Flux Balance Analysis to Decipher the Cell Metabolism |
| awards[0].id | https://openalex.org/G3788863026 |
| awards[0].funder_id | https://openalex.org/F4320309646 |
| awards[0].display_name | |
| awards[0].funder_award_id | 175323 |
| awards[0].funder_display_name | Virginia Polytechnic Institute and State University |
| biblio.issue | 4 |
| biblio.volume | 11 |
| biblio.last_page | e0154188 |
| biblio.first_page | e0154188 |
| topics[0].id | https://openalex.org/T10932 |
| topics[0].field.id | https://openalex.org/fields/13 |
| topics[0].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[0].score | 1.0 |
| topics[0].domain.id | https://openalex.org/domains/1 |
| topics[0].domain.display_name | Life Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1312 |
| topics[0].subfield.display_name | Molecular Biology |
| topics[0].display_name | Microbial Metabolic Engineering and Bioproduction |
| topics[1].id | https://openalex.org/T10621 |
| topics[1].field.id | https://openalex.org/fields/13 |
| topics[1].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[1].score | 0.9990000128746033 |
| topics[1].domain.id | https://openalex.org/domains/1 |
| topics[1].domain.display_name | Life Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1312 |
| topics[1].subfield.display_name | Molecular Biology |
| topics[1].display_name | Gene Regulatory Network Analysis |
| topics[2].id | https://openalex.org/T10887 |
| topics[2].field.id | https://openalex.org/fields/13 |
| topics[2].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[2].score | 0.9969000220298767 |
| topics[2].domain.id | https://openalex.org/domains/1 |
| topics[2].domain.display_name | Life Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1312 |
| topics[2].subfield.display_name | Molecular Biology |
| topics[2].display_name | Bioinformatics and Genomic Networks |
| funders[0].id | https://openalex.org/F4320309646 |
| funders[0].ror | https://ror.org/02smfhw86 |
| funders[0].display_name | Virginia Polytechnic Institute and State University |
| is_xpac | False |
| apc_list.value | 1805 |
| apc_list.currency | USD |
| apc_list.value_usd | 1805 |
| apc_paid.value | 1340 |
| apc_paid.currency | EUR |
| apc_paid.value_usd | 1445 |
| concepts[0].id | https://openalex.org/C167091322 |
| concepts[0].level | 2 |
| concepts[0].score | 0.8157919645309448 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q5463029 |
| concepts[0].display_name | Flux balance analysis |
| concepts[1].id | https://openalex.org/C157585117 |
| concepts[1].level | 2 |
| concepts[1].score | 0.6041202545166016 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q158666 |
| concepts[1].display_name | Omics |
| concepts[2].id | https://openalex.org/C70721500 |
| concepts[2].level | 1 |
| concepts[2].score | 0.5674307942390442 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q177005 |
| concepts[2].display_name | Computational biology |
| concepts[3].id | https://openalex.org/C162317418 |
| concepts[3].level | 4 |
| concepts[3].score | 0.5665523409843445 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q252857 |
| concepts[3].display_name | Transcriptome |
| concepts[4].id | https://openalex.org/C160941953 |
| concepts[4].level | 3 |
| concepts[4].score | 0.5414239764213562 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q6822342 |
| concepts[4].display_name | Metabolic flux analysis |
| concepts[5].id | https://openalex.org/C14036430 |
| concepts[5].level | 2 |
| concepts[5].score | 0.5240321755409241 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q3736076 |
| concepts[5].display_name | Function (biology) |
| concepts[6].id | https://openalex.org/C127716648 |
| concepts[6].level | 3 |
| concepts[6].score | 0.5150706171989441 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q104053 |
| concepts[6].display_name | Phenotype |
| concepts[7].id | https://openalex.org/C41008148 |
| concepts[7].level | 0 |
| concepts[7].score | 0.45708465576171875 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[7].display_name | Computer science |
| concepts[8].id | https://openalex.org/C21565614 |
| concepts[8].level | 2 |
| concepts[8].score | 0.45242512226104736 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q12149006 |
| concepts[8].display_name | Metabolomics |
| concepts[9].id | https://openalex.org/C2991704936 |
| concepts[9].level | 3 |
| concepts[9].score | 0.4342511296272278 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q1057 |
| concepts[9].display_name | Cell metabolism |
| concepts[10].id | https://openalex.org/C152662350 |
| concepts[10].level | 2 |
| concepts[10].score | 0.4338807463645935 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q815297 |
| concepts[10].display_name | Systems biology |
| concepts[11].id | https://openalex.org/C86803240 |
| concepts[11].level | 0 |
| concepts[11].score | 0.38786399364471436 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[11].display_name | Biology |
| concepts[12].id | https://openalex.org/C60644358 |
| concepts[12].level | 1 |
| concepts[12].score | 0.3608391582965851 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q128570 |
| concepts[12].display_name | Bioinformatics |
| concepts[13].id | https://openalex.org/C124101348 |
| concepts[13].level | 1 |
| concepts[13].score | 0.3386523127555847 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q172491 |
| concepts[13].display_name | Data mining |
| concepts[14].id | https://openalex.org/C62231903 |
| concepts[14].level | 2 |
| concepts[14].score | 0.16407087445259094 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q1057 |
| concepts[14].display_name | Metabolism |
| concepts[15].id | https://openalex.org/C1491633281 |
| concepts[15].level | 2 |
| concepts[15].score | 0.13210910558700562 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q7868 |
| concepts[15].display_name | Cell |
| concepts[16].id | https://openalex.org/C54355233 |
| concepts[16].level | 1 |
| concepts[16].score | 0.12489849328994751 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q7162 |
| concepts[16].display_name | Genetics |
| concepts[17].id | https://openalex.org/C55493867 |
| concepts[17].level | 1 |
| concepts[17].score | 0.08098816871643066 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q7094 |
| concepts[17].display_name | Biochemistry |
| concepts[18].id | https://openalex.org/C104317684 |
| concepts[18].level | 2 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q7187 |
| concepts[18].display_name | Gene |
| concepts[19].id | https://openalex.org/C150194340 |
| concepts[19].level | 3 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q26972 |
| concepts[19].display_name | Gene expression |
| keywords[0].id | https://openalex.org/keywords/flux-balance-analysis |
| keywords[0].score | 0.8157919645309448 |
| keywords[0].display_name | Flux balance analysis |
| keywords[1].id | https://openalex.org/keywords/omics |
| keywords[1].score | 0.6041202545166016 |
| keywords[1].display_name | Omics |
| keywords[2].id | https://openalex.org/keywords/computational-biology |
| keywords[2].score | 0.5674307942390442 |
| keywords[2].display_name | Computational biology |
| keywords[3].id | https://openalex.org/keywords/transcriptome |
| keywords[3].score | 0.5665523409843445 |
| keywords[3].display_name | Transcriptome |
| keywords[4].id | https://openalex.org/keywords/metabolic-flux-analysis |
| keywords[4].score | 0.5414239764213562 |
| keywords[4].display_name | Metabolic flux analysis |
| keywords[5].id | https://openalex.org/keywords/function |
| keywords[5].score | 0.5240321755409241 |
| keywords[5].display_name | Function (biology) |
| keywords[6].id | https://openalex.org/keywords/phenotype |
| keywords[6].score | 0.5150706171989441 |
| keywords[6].display_name | Phenotype |
| keywords[7].id | https://openalex.org/keywords/computer-science |
| keywords[7].score | 0.45708465576171875 |
| keywords[7].display_name | Computer science |
| keywords[8].id | https://openalex.org/keywords/metabolomics |
| keywords[8].score | 0.45242512226104736 |
| keywords[8].display_name | Metabolomics |
| keywords[9].id | https://openalex.org/keywords/cell-metabolism |
| keywords[9].score | 0.4342511296272278 |
| keywords[9].display_name | Cell metabolism |
| keywords[10].id | https://openalex.org/keywords/systems-biology |
| keywords[10].score | 0.4338807463645935 |
| keywords[10].display_name | Systems biology |
| keywords[11].id | https://openalex.org/keywords/biology |
| keywords[11].score | 0.38786399364471436 |
| keywords[11].display_name | Biology |
| keywords[12].id | https://openalex.org/keywords/bioinformatics |
| keywords[12].score | 0.3608391582965851 |
| keywords[12].display_name | Bioinformatics |
| keywords[13].id | https://openalex.org/keywords/data-mining |
| keywords[13].score | 0.3386523127555847 |
| keywords[13].display_name | Data mining |
| keywords[14].id | https://openalex.org/keywords/metabolism |
| keywords[14].score | 0.16407087445259094 |
| keywords[14].display_name | Metabolism |
| keywords[15].id | https://openalex.org/keywords/cell |
| keywords[15].score | 0.13210910558700562 |
| keywords[15].display_name | Cell |
| keywords[16].id | https://openalex.org/keywords/genetics |
| keywords[16].score | 0.12489849328994751 |
| keywords[16].display_name | Genetics |
| keywords[17].id | https://openalex.org/keywords/biochemistry |
| keywords[17].score | 0.08098816871643066 |
| keywords[17].display_name | Biochemistry |
| language | en |
| locations[0].id | doi:10.1371/journal.pone.0154188 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S202381698 |
| locations[0].source.issn | 1932-6203 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1932-6203 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | PLoS ONE |
| locations[0].source.host_organization | https://openalex.org/P4310315706 |
| locations[0].source.host_organization_name | Public Library of Science |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310315706 |
| locations[0].source.host_organization_lineage_names | Public Library of Science |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0154188&type=printable |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | PLOS ONE |
| locations[0].landing_page_url | https://doi.org/10.1371/journal.pone.0154188 |
| locations[1].id | pmid:27100883 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | PloS one |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/27100883 |
| locations[2].id | pmh:oai:RePEc:plo:pone00:0154188 |
| locations[2].is_oa | False |
| locations[2].source.id | https://openalex.org/S4306401271 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | RePEc: Research Papers in Economics |
| locations[2].source.host_organization | https://openalex.org/I77793887 |
| locations[2].source.host_organization_name | Federal Reserve Bank of St. Louis |
| locations[2].source.host_organization_lineage | https://openalex.org/I77793887 |
| locations[2].license | |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | article |
| locations[2].license_id | |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | |
| locations[2].landing_page_url | https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0154188 |
| locations[3].id | pmh:oai:doaj.org/article:d6db590140cf43af9ea4223e1f5f7046 |
| locations[3].is_oa | True |
| locations[3].source.id | https://openalex.org/S4306401280 |
| locations[3].source.issn | |
| locations[3].source.type | repository |
| locations[3].source.is_oa | False |
| locations[3].source.issn_l | |
| locations[3].source.is_core | False |
| locations[3].source.is_in_doaj | False |
| locations[3].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[3].source.host_organization | |
| locations[3].source.host_organization_name | |
| locations[3].license | cc-by-sa |
| locations[3].pdf_url | |
| locations[3].version | submittedVersion |
| locations[3].raw_type | article |
| locations[3].license_id | https://openalex.org/licenses/cc-by-sa |
| locations[3].is_accepted | False |
| locations[3].is_published | False |
| locations[3].raw_source_name | PLoS ONE, Vol 11, Iss 4, p e0154188 (2016) |
| locations[3].landing_page_url | https://doaj.org/article/d6db590140cf43af9ea4223e1f5f7046 |
| locations[4].id | pmh:oai:figshare.com:article/3192865 |
| locations[4].is_oa | True |
| locations[4].source.id | https://openalex.org/S4306400572 |
| locations[4].source.issn | |
| locations[4].source.type | repository |
| locations[4].source.is_oa | False |
| locations[4].source.issn_l | |
| locations[4].source.is_core | False |
| locations[4].source.is_in_doaj | False |
| locations[4].source.display_name | OPAL (Open@LaTrobe) (La Trobe University) |
| locations[4].source.host_organization | https://openalex.org/I196829312 |
| locations[4].source.host_organization_name | La Trobe University |
| locations[4].source.host_organization_lineage | https://openalex.org/I196829312 |
| locations[4].license | cc-by |
| locations[4].pdf_url | |
| locations[4].version | submittedVersion |
| locations[4].raw_type | Dataset |
| locations[4].license_id | https://openalex.org/licenses/cc-by |
| locations[4].is_accepted | False |
| locations[4].is_published | False |
| locations[4].raw_source_name | |
| locations[4].landing_page_url | https://figshare.com/articles/dataset/OM_FBA_Integrate_Transcriptomics_Data_with_Flux_Balance_Analysis_to_Decipher_the_Cell_Metabolism/3192865 |
| locations[5].id | pmh:oai:pubmedcentral.nih.gov:4839607 |
| locations[5].is_oa | True |
| locations[5].source.id | https://openalex.org/S2764455111 |
| locations[5].source.issn | |
| locations[5].source.type | repository |
| locations[5].source.is_oa | False |
| locations[5].source.issn_l | |
| locations[5].source.is_core | False |
| locations[5].source.is_in_doaj | False |
| locations[5].source.display_name | PubMed Central |
| locations[5].source.host_organization | https://openalex.org/I1299303238 |
| locations[5].source.host_organization_name | National Institutes of Health |
| locations[5].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[5].license | cc-by |
| locations[5].pdf_url | |
| locations[5].version | submittedVersion |
| locations[5].raw_type | Text |
| locations[5].license_id | https://openalex.org/licenses/cc-by |
| locations[5].is_accepted | False |
| locations[5].is_published | False |
| locations[5].raw_source_name | |
| locations[5].landing_page_url | http://doi.org/10.1371/journal.pone.0154188 |
| locations[6].id | pmh:oai:vtechworks.lib.vt.edu:10919/78380 |
| locations[6].is_oa | True |
| locations[6].source.id | https://openalex.org/S4306400248 |
| locations[6].source.issn | |
| locations[6].source.type | repository |
| locations[6].source.is_oa | False |
| locations[6].source.issn_l | |
| locations[6].source.is_core | False |
| locations[6].source.is_in_doaj | False |
| locations[6].source.display_name | VTechWorks (Virginia Tech) |
| locations[6].source.host_organization | https://openalex.org/I859038795 |
| locations[6].source.host_organization_name | Virginia Tech |
| locations[6].source.host_organization_lineage | https://openalex.org/I859038795 |
| locations[6].license | cc-by |
| locations[6].pdf_url | |
| locations[6].version | submittedVersion |
| locations[6].raw_type | Text |
| locations[6].license_id | https://openalex.org/licenses/cc-by |
| locations[6].is_accepted | False |
| locations[6].is_published | False |
| locations[6].raw_source_name | |
| locations[6].landing_page_url | http://hdl.handle.net/10919/78380 |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5102763028 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-2380-9270 |
| authorships[0].author.display_name | Weihua Guo |
| authorships[0].countries | US |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I859038795 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Biological Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America |
| authorships[0].institutions[0].id | https://openalex.org/I859038795 |
| authorships[0].institutions[0].ror | https://ror.org/02smfhw86 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I859038795 |
| authorships[0].institutions[0].country_code | US |
| authorships[0].institutions[0].display_name | Virginia Tech |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Weihua Guo |
| authorships[0].is_corresponding | True |
| authorships[0].raw_affiliation_strings | Department of Biological Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America |
| authorships[1].author.id | https://openalex.org/A5101929118 |
| authorships[1].author.orcid | https://orcid.org/0000-0003-4426-5732 |
| authorships[1].author.display_name | Xueyang Feng |
| authorships[1].countries | US |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I859038795 |
| authorships[1].affiliations[0].raw_affiliation_string | Department of Biological Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America |
| authorships[1].institutions[0].id | https://openalex.org/I859038795 |
| authorships[1].institutions[0].ror | https://ror.org/02smfhw86 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I859038795 |
| authorships[1].institutions[0].country_code | US |
| authorships[1].institutions[0].display_name | Virginia Tech |
| authorships[1].author_position | last |
| authorships[1].raw_author_name | Xueyang Feng |
| authorships[1].is_corresponding | True |
| authorships[1].raw_affiliation_strings | Department of Biological Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0154188&type=printable |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | OM-FBA: Integrate Transcriptomics Data with Flux Balance Analysis to Decipher the Cell Metabolism |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10932 |
| primary_topic.field.id | https://openalex.org/fields/13 |
| primary_topic.field.display_name | Biochemistry, Genetics and Molecular Biology |
| primary_topic.score | 1.0 |
| primary_topic.domain.id | https://openalex.org/domains/1 |
| primary_topic.domain.display_name | Life Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1312 |
| primary_topic.subfield.display_name | Molecular Biology |
| primary_topic.display_name | Microbial Metabolic Engineering and Bioproduction |
| related_works | https://openalex.org/W4302564615, https://openalex.org/W2963238982, https://openalex.org/W2796870706, https://openalex.org/W2909696795, https://openalex.org/W2990176998, https://openalex.org/W1999460937, https://openalex.org/W2146126338, https://openalex.org/W2046546139, https://openalex.org/W2613838074, https://openalex.org/W2133150343 |
| cited_by_count | 25 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 2 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 5 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 1 |
| counts_by_year[3].year | 2022 |
| counts_by_year[3].cited_by_count | 3 |
| counts_by_year[4].year | 2021 |
| counts_by_year[4].cited_by_count | 2 |
| counts_by_year[5].year | 2020 |
| counts_by_year[5].cited_by_count | 2 |
| counts_by_year[6].year | 2019 |
| counts_by_year[6].cited_by_count | 3 |
| counts_by_year[7].year | 2018 |
| counts_by_year[7].cited_by_count | 2 |
| counts_by_year[8].year | 2017 |
| counts_by_year[8].cited_by_count | 5 |
| locations_count | 7 |
| best_oa_location.id | doi:10.1371/journal.pone.0154188 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S202381698 |
| best_oa_location.source.issn | 1932-6203 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1932-6203 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | PLoS ONE |
| best_oa_location.source.host_organization | https://openalex.org/P4310315706 |
| best_oa_location.source.host_organization_name | Public Library of Science |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310315706 |
| best_oa_location.source.host_organization_lineage_names | Public Library of Science |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0154188&type=printable |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | PLOS ONE |
| best_oa_location.landing_page_url | https://doi.org/10.1371/journal.pone.0154188 |
| primary_location.id | doi:10.1371/journal.pone.0154188 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S202381698 |
| primary_location.source.issn | 1932-6203 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1932-6203 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | PLoS ONE |
| primary_location.source.host_organization | https://openalex.org/P4310315706 |
| primary_location.source.host_organization_name | Public Library of Science |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310315706 |
| primary_location.source.host_organization_lineage_names | Public Library of Science |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0154188&type=printable |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | PLOS ONE |
| primary_location.landing_page_url | https://doi.org/10.1371/journal.pone.0154188 |
| publication_date | 2016-04-21 |
| publication_year | 2016 |
| referenced_works | https://openalex.org/W2171214502, https://openalex.org/W2122828981, https://openalex.org/W2015751324, https://openalex.org/W2094700891, https://openalex.org/W2022603493, https://openalex.org/W2118526609, https://openalex.org/W1981509058, https://openalex.org/W1538574688, https://openalex.org/W2142923621, https://openalex.org/W2170892735, https://openalex.org/W1975721281, https://openalex.org/W2084151531, https://openalex.org/W1968449541, https://openalex.org/W2063398237, https://openalex.org/W2078355959, https://openalex.org/W2097664794, https://openalex.org/W2096097217, https://openalex.org/W2113365252, https://openalex.org/W2120845681, https://openalex.org/W2162666840, https://openalex.org/W2172129062, https://openalex.org/W2141360045, https://openalex.org/W1998633945, https://openalex.org/W2021513917, https://openalex.org/W2014482592, https://openalex.org/W1971125717, https://openalex.org/W2065104071, https://openalex.org/W2133376865, https://openalex.org/W2103041540, https://openalex.org/W1651496407, https://openalex.org/W2019293073, https://openalex.org/W2168546553, https://openalex.org/W2053118024, https://openalex.org/W2048214825, https://openalex.org/W2202347610, https://openalex.org/W2044692345, https://openalex.org/W2077046573, https://openalex.org/W2171327609, https://openalex.org/W1970970926, https://openalex.org/W2008087600, https://openalex.org/W2030955639, https://openalex.org/W2094678200, https://openalex.org/W2118258530, https://openalex.org/W6677946334, https://openalex.org/W4239942645, https://openalex.org/W2106945333, https://openalex.org/W2069860553, https://openalex.org/W2191886898, https://openalex.org/W2030776070, https://openalex.org/W2102314894, https://openalex.org/W2111421616, https://openalex.org/W2171338658, https://openalex.org/W4388651733, https://openalex.org/W4294326454, https://openalex.org/W2042459594, https://openalex.org/W2120358246, https://openalex.org/W2436303151, https://openalex.org/W2218367612, https://openalex.org/W4211085285, https://openalex.org/W90244446 |
| referenced_works_count | 60 |
| abstract_inverted_index.a | 70, 118, 224 |
| abstract_inverted_index.In | 92 |
| abstract_inverted_index.S. | 185 |
| abstract_inverted_index.To | 63 |
| abstract_inverted_index.We | 115, 176 |
| abstract_inverted_index.an | 124 |
| abstract_inverted_index.as | 4, 112, 215 |
| abstract_inverted_index.at | 173 |
| abstract_inverted_index.be | 47, 194, 235 |
| abstract_inverted_index.by | 204, 241 |
| abstract_inverted_index.in | 49, 180, 197 |
| abstract_inverted_index.is | 58 |
| abstract_inverted_index.of | 36, 52, 137, 184, 199, 218 |
| abstract_inverted_index.on | 29 |
| abstract_inverted_index.to | 13, 18, 76, 84, 122, 132, 158, 168, 227 |
| abstract_inverted_index.we | 67, 94 |
| abstract_inverted_index.FBA | 30, 50, 83, 128 |
| abstract_inverted_index.GEO | 106 |
| abstract_inverted_index.The | 144 |
| abstract_inverted_index.and | 21, 31, 99, 187, 209, 233 |
| abstract_inverted_index.for | 60, 108, 127 |
| abstract_inverted_index.has | 9 |
| abstract_inverted_index.its | 19 |
| abstract_inverted_index.may | 44 |
| abstract_inverted_index.not | 45 |
| abstract_inverted_index.the | 34, 54, 133, 138, 152, 160, 190, 200, 216, 243, 248 |
| abstract_inverted_index.via | 155 |
| abstract_inverted_index.was | 148, 165 |
| abstract_inverted_index.been | 10, 26 |
| abstract_inverted_index.cell | 15, 61, 171 |
| abstract_inverted_index.data | 79, 98, 101, 154, 207, 231 |
| abstract_inverted_index.flux | 5, 219 |
| abstract_inverted_index.from | 102 |
| abstract_inverted_index.have | 25, 68, 177 |
| abstract_inverted_index.high | 90 |
| abstract_inverted_index.into | 82 |
| abstract_inverted_index.lead | 131 |
| abstract_inverted_index.most | 134, 198 |
| abstract_inverted_index.next | 149, 166 |
| abstract_inverted_index.such | 3, 111, 214 |
| abstract_inverted_index.that | 57, 129, 189 |
| abstract_inverted_index.then | 116 |
| abstract_inverted_index.this | 65 |
| abstract_inverted_index.used | 12, 167 |
| abstract_inverted_index.with | 89, 151, 237, 247 |
| abstract_inverted_index.(FBA) | 8 |
| abstract_inverted_index.(e.g. | 80, 105, 141 |
| abstract_inverted_index.based | 28 |
| abstract_inverted_index.cases | 201 |
| abstract_inverted_index.could | 130, 193, 234 |
| abstract_inverted_index.first | 95 |
| abstract_inverted_index.found | 188 |
| abstract_inverted_index.known | 139 |
| abstract_inverted_index.novel | 71, 225 |
| abstract_inverted_index.omFBA | 179, 222 |
| abstract_inverted_index.other | 238 |
| abstract_inverted_index.sugar | 182 |
| abstract_inverted_index.their | 41 |
| abstract_inverted_index.tools | 240 |
| abstract_inverted_index.using | 53, 205 |
| abstract_inverted_index.which | 164 |
| abstract_inverted_index.yield | 192 |
| abstract_inverted_index.(>80%) | 203 |
| abstract_inverted_index.Match" | 120 |
| abstract_inverted_index.Thanks | 17 |
| abstract_inverted_index.alone, | 208 |
| abstract_inverted_index.always | 46 |
| abstract_inverted_index.derive | 123 |
| abstract_inverted_index.namely | 74 |
| abstract_inverted_index.obtain | 85 |
| abstract_inverted_index.omFBA, | 75 |
| abstract_inverted_index.tested | 202 |
| abstract_inverted_index.widely | 11 |
| abstract_inverted_index.applied | 178 |
| abstract_inverted_index.assumed | 59 |
| abstract_inverted_index.balance | 6 |
| abstract_inverted_index.because | 51 |
| abstract_inverted_index.derived | 145 |
| abstract_inverted_index.ethanol | 142, 191 |
| abstract_inverted_index.ratios. | 220 |
| abstract_inverted_index.unknown | 174 |
| abstract_inverted_index.various | 37 |
| abstract_inverted_index.yield). | 143 |
| abstract_inverted_index.However, | 40 |
| abstract_inverted_index.Overall, | 221 |
| abstract_inverted_index.accurate | 48, 135 |
| abstract_inverted_index.analysis | 7, 157 |
| abstract_inverted_index.database | 104 |
| abstract_inverted_index.dynamics | 217 |
| abstract_inverted_index.function | 56, 126, 147, 246 |
| abstract_inverted_index.general, | 93 |
| abstract_inverted_index.generate | 159 |
| abstract_inverted_index.insights | 213 |
| abstract_inverted_index.modeling | 2 |
| abstract_inverted_index.numerous | 23 |
| abstract_inverted_index.overcome | 64 |
| abstract_inverted_index.platform | 226 |
| abstract_inverted_index.presents | 223 |
| abstract_inverted_index.revealed | 210 |
| abstract_inverted_index.simulate | 14, 170 |
| abstract_inverted_index.studying | 181 |
| abstract_inverted_index.systems. | 39 |
| abstract_inverted_index.valuable | 211 |
| abstract_inverted_index.accuracy. | 91 |
| abstract_inverted_index.algorithm | 121 |
| abstract_inverted_index.arbitrary | 244 |
| abstract_inverted_index.collected | 96 |
| abstract_inverted_index.database) | 107 |
| abstract_inverted_index.developed | 27, 69, 117 |
| abstract_inverted_index.different | 109 |
| abstract_inverted_index.function, | 163 |
| abstract_inverted_index.functions | 88 |
| abstract_inverted_index.integrate | 77, 229 |
| abstract_inverted_index.metabolic | 1, 212 |
| abstract_inverted_index.objective | 55, 87, 125, 146, 162, 245, 250 |
| abstract_inverted_index.phenotype | 42, 100, 140 |
| abstract_inverted_index.predicted | 33, 196 |
| abstract_inverted_index.published | 103 |
| abstract_inverted_index.replacing | 242 |
| abstract_inverted_index."Phenotype | 119 |
| abstract_inverted_index.accurately | 169, 195 |
| abstract_inverted_index.algorithms | 24 |
| abstract_inverted_index.biological | 38 |
| abstract_inverted_index.cerevisiae | 186 |
| abstract_inverted_index.challenge, | 66 |
| abstract_inverted_index.correlated | 150 |
| abstract_inverted_index.estimation | 136 |
| abstract_inverted_index.framework, | 73 |
| abstract_inverted_index.functions. | 251 |
| abstract_inverted_index.metabolism | 172, 183 |
| abstract_inverted_index.phenotypes | 35 |
| abstract_inverted_index.regression | 156 |
| abstract_inverted_index.simplicity | 20 |
| abstract_inverted_index.FBA-derived | 239 |
| abstract_inverted_index.cerevisiae. | 114 |
| abstract_inverted_index.conditions. | 175 |
| abstract_inverted_index.metabolism. | 16, 62 |
| abstract_inverted_index.multi-omics | 78, 230 |
| abstract_inverted_index.potentially | 228 |
| abstract_inverted_index.predictions | 43 |
| abstract_inverted_index.flexibility, | 22 |
| abstract_inverted_index.incorporated | 236 |
| abstract_inverted_index.omics-guided | 86, 161, 249 |
| abstract_inverted_index.successfully | 32 |
| abstract_inverted_index.Saccharomyces | 113 |
| abstract_inverted_index.computational | 72 |
| abstract_inverted_index.microorganisms | 110 |
| abstract_inverted_index.simultaneously | 232 |
| abstract_inverted_index.transcriptomics | 97, 153, 206 |
| abstract_inverted_index.Constraint-based | 0 |
| abstract_inverted_index.transcriptomics) | 81 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5102763028, https://openalex.org/A5101929118 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| corresponding_institution_ids | https://openalex.org/I859038795 |
| citation_normalized_percentile.value | 0.85621642 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |