Computational approaches for microalgal biofuel optimization: A review

BioMed Research International

Volumn 2014, Issue , 2014, Pages

  Koussa, Joseph ^a   Chaiboonchoe, Amphun ^a   Salehi Ashtiani, Kourosh ^a  

^a NEW YORK UNIVERSITY ABU DHABI   (United Arab Emirates)

Author keywords

[No Author keywords available]

Indexed keywords

BIOFUEL;

ACARYOCHLORIS MARINA; ANABAENA CYLINDRICA; ANABAENA VARIABILIS; BIOFUEL PRODUCTION; CHLAMYDOMONAS REINHARDTII; ENTAMOEBA COLI; INTRACELLULAR SPACE; MASS ACTION; METABOLIC FLUX ANALYSIS; METABOLISM; METABOLOMICS; MICROALGA; MOLECULAR INTERACTION; NANNOCHLOROPSIS GADITANA; NONHUMAN; RENEWABLE ENERGY; REVIEW; SYNECHOCOCCUS ELONGATUS; THALASSIOSIRA PSEUDONANA; BIOLOGY; MICROBIOLOGY; PROCEDURES; THEORETICAL MODEL;

BIOFUELS; COMPUTATIONAL BIOLOGY; METABOLIC FLUX ANALYSIS; METABOLIC NETWORKS AND PATHWAYS; MICROALGAE; MODELS, THEORETICAL;

EID: 84912544153     PISSN: 23146133     EISSN: 23146141     Source Type: Journal    
DOI: 10.1155/2014/649453     Document Type: Review

References (87)

1. Koskimaki J. E., Blazier A. S., Clarens A. F., Papin J. A., Computational models of algae metabolism for industrial applications. Industrial Biotechnology 2013 9 4 185 195 10.1089/ind.2013.0012 2-s2.0-84881515127
2. Usaite R., Patil K. R., Grotkjær T., Nielsen J., Regenberg B., Global transcriptional and physiological responses of Saccharomyces cerevisiae to ammonium, L-alanine, or L-glutamine limitation. Applied and Environmental Microbiology 2006 72 9 6194 6203 10.1128/AEM.00548-06 2-s2.0-33748766328
3. Zelle R. M., de Hulster E., van Winden W. A., de Waard P., Dijkema C., Winkler A. A., Geertman J.-M. A., van Dijken J. P., Pronk J. T., van Maris A. J. A., Malic acid production by Saccharomyces cerevisiae: engineering of pyruvate carboxylation, oxaloacetate reduction, and malate export. Applied and Environmental Microbiology 2008 74 9 2766 2777 10.1128/AEM.02591-07 2-s2.0-43049090802
4. Izallalen M., Mahadevan R., Burgard A., Postier B., Didonato R. Jr., Sun J., Schilling C. H., Lovley D. R., Geobacter sulfurreducens strain engineered for increased rates of respiration. Metabolic Engineering 2008 10 5 267 275 10.1016/j.ymben.2008.06.005 2-s2.0-50549104615
5. Oberhardt M. A., Palsson B. Ø., Papin J. A., Applications of genome-scale metabolic reconstructions. Molecular Systems Biology 2009 5 1, article 320 10.1038/msb.2009.77 2-s2.0-73149122136
6. Karp P. D., Paley S. M., Krummenacker M., Latendresse M., Dale J. M., Lee T. J., Kaipa P., Gilham F., Spaulding A., Popescu L., Altman T., Paulsen I., Keseler I. M., Caspi R., Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology. Briefings in Bioinformatics 2009 11 1 40 79 bbp043 10.1093/bib/bbp043 2-s2.0-75849133666
7. Schomburg I., Chang A., Placzek S., Söhngen C., Rother M., Lang M., Munaretto C., Ulas S., Stelzer M., Grote A., Scheer M., Schomburg D., BRENDA in 2013: integrated reactions, kinetic data, enzyme function data, improved disease classification: new options and contents in BRENDA. Nucleic Acids Research 2013 41 1 D764 D772 10.1093/nar/gks1049 2-s2.0-84876522835
8. Artimo P., Jonnalagedda M., Arnold K., Baratin D., Csardi G., De Castro E., Duvaud S., Flegel V., Fortier A., Gasteiger E., Grosdidier A., Hernandez C., Ioannidis V., Kuznetsov D., Liechti R., Moretti S., Mostaguir K., Redaschi N., Rossier G., Xenarios I., Stockinger H., ExPASy: SIB bioinformatics resource portal. Nucleic Acids Research 2012 40 1 W597 W603 10.1093/nar/gks400 2-s2.0-84864434718
9. Consortium T. U., Ongoing and future developments at the Universal Protein Resource. Nucleic Acids Research 2011 39 supplement 1 D214 D219
10. Caspi R., Altman T., Billington R., Dreher K., Foerster H., Fulcher C. A., Holland T. A., Keseler I. M., Kothari A., Kubo A., Krummenacker M., Latendresse M., Mueller L. A., Ong Q., Paley S., Subhraveti P., Weaver D. S., Weerasinghe D., Zhang P., Karp P. D., The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome databases. Nucleic Acids Research 2014 42 1 D459 D471 10.1093/nar/gkt1103 2-s2.0-84891774001
11. Kanehisa M., Goto S., Sato Y., Furumichi M., Tanabe M., KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Research 2012 40 1 D109 D114 10.1093/nar/gkr988 2-s2.0-84858983547
12. Croft D., O'Kelly G., Wu G., Haw R., Gillespie M., Matthews L., Caudy M., Garapati P., Gopinath G., Jassal B., Jupe S., Kalatskaya I., MayMahajan S., May B., Ndegwa N., Schmidt E., Shamovsky V., Yung C., Birney E., Hermjakob H., D'Eustachio P., Stein L., Reactome: a database of reactions, pathways and biological processes. Nucleic Acids Research 2011 39 supplement 1 D691 D697 10.1093/nar/gkq1018 2-s2.0-78651275182
13. Schellenberger J., Park J. O., Conrad T. M., Palsson B. T., BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions. BMC Bioinformatics 2010 11, article 213 10.1186/1471-2105-11-213 2-s2.0-77951612556
14. Becker S. A., Feist A. M., Mo M. L., Hannum G., Palsson B. Ø., Herrgard M. J., Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox. Nature Protocols 2007 2 3 727 738 10.1038/nprot.2007.99 2-s2.0-34347258175
15. Schellenberger J., Que R., Fleming R. M. T., Thiele I., Orth J. D., Feist A. M., Zielinski D. C., Bordbar A., Lewis N. E., Rahmanian S., Kang J., Hyduke D. R., Palsson B. Ø., Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0. Nature Protocols 2011 6 9 1290 1307 10.1038/nprot.2011.308 2-s2.0-79551662521
16. Thorleifsson S. G., Thiele I., rBioNet: a COBRA toolbox extension for reconstructing high-quality biochemical networks. Bioinformatics 2011 27 14 2009 2010 btr308 10.1093/bioinformatics/btr308 2-s2.0-79960126760
17. Devoid S., Overbeek R., DeJongh M., Automated genome annotation and metabolic model reconstruction in the SEED and model SEED. Systems Metabolic Engineering 2013 17 45 10.1007/978-1-62703-299-5-2
18. Karp P. D., Paley S., Romero P., The pathway tools software. Bioinformatics 2002 18 supplement 1 S225 S232 10.1093/bioinformatics/18.suppl-1.S225 2-s2.0-11244328060
19. Caspi R., Altman T., Dale J. M., Dreher K., Fulcher C. A., Gilham F., Kaipa P., Karthikeyan A. S., Kothari A., Krummenacker M., Latendresse M., Mueller L. A., Paley S., Popescu L., Pujar A., Shearer A. G., Zhang P., Karp P. D., The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Research 2009 38 supplement 1 D473 D479 gkp875 10.1093/nar/gkp875 2-s2.0-75549090505
20. Caspi R., Altman T., Dreher K., Fulcher C. A., Subhraveti P., Keseler I. M., Kothari A., Krummenacker M., Latendresse M., Mueller L. A., Ong Q., Paley S., Pujar A., Shearer A. G., Travers M., Weerasinghe D., Zhang P., Karp P. D., The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Research 2012 40 1 D742 D753 10.1093/nar/gkr1014 2-s2.0-84860490976
21. Caspi R., Foerster H., Fulcher C. A., Kaipa P., Krummenacker M., Latendresse M., Paley S., Rhee S. Y., Shearer A. G., Tissier C., Walk T. C., Zhang P., Karp P. D., The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome databases. Nucleic Acids Research 2008 36, supplement 1 D623 D631 10.1093/nar/gkm900 2-s2.0-38549117301
22. Kasprzyk A., BioMart: driving a paradigm change in biological data management. Database 2011 2011 bar049 10.1093/database/bar049 2-s2.0-84858314394
23. Kim T. Y., Sohn S. B., Kim Y. B., Kim W. J., Lee S. Y., Recent advances in reconstruction and applications of genome-scale metabolic models. Current Opinion in Biotechnology 2012 23 4 617 623 10.1016/j.copbio.2011.10.007 2-s2.0-84864795465
24. Oberhardt M. A., Puchałka J., dos Santos V. A. P. M., Papin J. A., Reconciliation of genome-scale metabolic reconstructions for comparative systems analysis. PLoS Computational Biology 2011 7 3 e1001116 10.1371/journal.pcbi.1001116 2-s2.0-79953649492
25. Thiele I., Palsson B. Ø., A protocol for generating a high-quality genome-scale metabolic reconstruction. Nature Protocols 2010 5 1 93 121 10.1038/nprot.2009.203 2-s2.0-75149129569
26. Notebaart R. A., van Enckevort F. H. J., Francke C., Siezen R. J., Teusink B., Accelerating the reconstruction of genome-scale metabolic networks. BMC Bioinformatics 2006 7, article 296 10.1186/1471-2105-7-296 2-s2.0-33747620056
27. Liao Y.-C., Tsai M.-H., Chen F.-C., Hsiung C. A., GEMSiRV: a software platform for GEnome-scale metabolic model simulation, reconstruction and visualization. Bioinformatics 2012 28 13 1752 1758 bts267 10.1093/bioinformatics/bts267 2-s2.0-84864000794
28. Feng X., Xu Y., Chen Y., Tang Y. J., MicrobesFlux: a web platform for drafting metabolic models from the KEGG database. BMC Systems Biology 2012 6, article 94 10.1186/1752-0509-6-94 2-s2.0-84864464109
29. Kumar A., Suthers P. F., Maranas C. D., MetRxn: A knowledgebase of metabolites and reactions spanning metabolic models and databases. BMC Bioinformatics 2012 13 1, article 6 10.1186/1471-2105-13-6 2-s2.0-84855499408
30. Henry C. S., Dejongh M., Best A. A., Frybarger P. M., Linsay B., Stevens R. L., High-throughput generation, optimization and analysis of genome-scale metabolic models. Nature Biotechnology 2010 28 9 977 982 10.1038/nbt.1672 2-s2.0-77956696072
31. Swainston N., Smallbone K., Mendes P., Kell D., Paton N., The SuBliMinaL Toolbox: automating steps in the reconstruction of metabolic networks. Journal of Integrative Bioinformatics 2011 8 2 article 186 2-s2.0-84856038703
32. Boele J., Olivier B. G., Teusink B., FAME, the flux analysis and modeling environment. BMC Systems Biology 2012 6 1 8 10.1186/1752-0509-6-8 2-s2.0-84863806415
33. Agren R., Liu L., Shoaie S., Vongsangnak W., Nookaew I., Nielsen J., The RAVEN toolbox and its use for generating a genome-scale metabolic model for penicillium chrysogenum. PLoS Computational Biology 2013 9 3 e1002980 10.1371/journal.pcbi.1002980 2-s2.0-84875973063
34. Hamilton J. J., Reed J. L., Software platforms to facilitate reconstructing genome-scale metabolic networks. Environmental Microbiology 2014 16 1 49 59 10.1111/1462-2920.12312 2-s2.0-84891635463
35. Altman T., Travers M., Kothari A., Caspi R., Karp P. D., A systematic comparison of the MetaCyc and KEGG pathway databases. BMC Bioinformatics 2013 14, article 112 10.1186/1471-2105-14-112 2-s2.0-84875317202
36. Smoot M. E., Ono K., Ruscheinski J., Wang P.-L., Ideker T., Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 2011 27 3 431 432 10.1093/bioinformatics/btq675 2-s2.0-79551587720
37. Saito R., Smoot M. E., Ono K., Ruscheinski J., Wang P.-L., Lotia S., Pico A. R., Bader G. D., Ideker T., A travel guide to Cytoscape plugins. Nature Methods 2012 9 11 1069 1076 10.1038/nmeth.2212 2-s2.0-84869054051
38. DeJongh M., Bockstege B., Frybarger P., Hazekamp N., Kammeraad J., McGeehan T., CytoSEED: a Cytoscape plugin for viewing, manipulating and analyzing metabolic models created by the model SEED. Bioinformatics 2012 28 6 891 892 10.1093/bioinformatics/btr719 2-s2.0-84859057484
39. König M., Holzhütter H., Fluxviz-cytoscape plug-in for visualization of flux distributions in networks. Proceedings of the International Conference on Genome Informatics 2010
40. Rohn H., Junker A., Hartmann A., Grafahrend-Belau E., Treutler H., Klapperstück M., Czauderna T., Klukas C., Schreiber F., VANTED v2: a framework for systems biology applications. BMC Systems Biology 2012 6, article 139 10.1186/1752-0509-6-139 2-s2.0-84868514445
41. Junker B. H., Klukas C., Schreiber F., Vanted: a system for advanced data analysis and visualization in the context of biological networks. BMC Bioinformatics 2006 7, article 109 13 10.1186/1471-2105-7-109 2-s2.0-33645241830
42. Rohn H., Hartmann A., Junker A., Junker B. H., Schreiber F., FluxMap: A VANTED add-on for the visual exploration of flux distributions in biological networks. BMC Systems Biology 2012 6, article 33 10.1186/1752-0509-6-33 2-s2.0-84862157783
43. Grafahrend-Belau E., Klukas C., Junker B. H., Schreiber F., FBA-SimVis: interactive visualization of constraint-based metabolic models. Bioinformatics 2009 25 20 2755 2757 10.1093/bioinformatics/btp408 2-s2.0-70350029519
44. Kostromins A., Stalidzans E., Paint4Net: COBRA Toolbox extension for visualization of stoichiometric models of metabolism. BioSystems 2012 109 2 233 239 10.1016/j.biosystems.2012.03.002 2-s2.0-84863432704
45. Jenseny P. A., Papin J. A., MetDraw: automated visualization of genome-scale metabolic network reconstructions and high-throughput data. Bioinformatics 2014 30 9 1327 1328 10.1093/bioinformatics/btt758 2-s2.0-84899544870
46. Satish Kumar V., Dasika M. S., Maranas C. D., Optimization based automated curation of metabolic reconstructions. BMC Bioinformatics 2007 8, article 212 10.1186/1471-2105-8-212 2-s2.0-34547676311
47. Kharchenko P., Vitkup D., Church G. M., Filling gaps in a metabolic network using expression information. Bioinformatics 2004 20 supplement 1 i178 i185 10.1093/bioinformatics/bth930 2-s2.0-24744467372
48. Green M. L., Karp P. D., A Bayesian method for identifying missing enzymes in predicted metabolic pathway databases. BMC Bioinformatics 2004 5, article 76 10.1186/1471-2105-5-76 2-s2.0-13244268322
49. Kumar V. S., Maranas C. D., GrowMatch: an automated method for reconciling In Silico / In Vivo growth predictions. PLoS Computational Biology 2009 5 3 10.1371/journal.pcbi.1000308 2-s2.0-63549108441
50. Hatzimanikatis V., Li C., Ionita J. A., Henry C. S., Jankowski M. D., Broadbelt L. J., Exploring the diversity of complex metabolic networks. Bioinformatics 2005 21 8 1603 1609 10.1093/bioinformatics/bti213 2-s2.0-17444382016
51. Lakshmanan M., Koh G., Chung B. K. S., Lee D.-Y., Software applications for flux balance analysis. Briefings in Bioinformatics 2014 15 1 108 122 10.1093/bib/bbs069 2-s2.0-84892991094
52. Becker S. A., Palsson B. O., Context-specific metabolic networks are consistent with experiments. PLoS Computational Biology 2008 4 5 e1000082 10.1371/journal.pcbi.1000082 MR2407501 2-s2.0-44949225040
53. Blazier A. S., Papin J. A., Integration of expression data in genome-scale metabolic network reconstructions. Frontiers in Physiology 2012 3, article 299 10.3389/fphys.2012.00299 2-s2.0-84866487453
54. Machado D., Herrgård M., Systematic evaluation of methods for integration of transcriptomic data into constraint-based models of metabolism. PLoS Computational Biology 2014 10 4 e1003580 10.1371/journal.pcbi.1003580 2-s2.0-84901306814
55. Zur H., Ruppin E., Shlomi T., iMAT: an integrative metabolic analysis tool. Bioinformatics 2010 26 24 3140 3142 10.1093/bioinformatics/btq602 2-s2.0-79951745716
56. Jensen P. A., Papin J. A., Functional integration of a metabolic network model and expression data without arbitrary thresholding. Bioinformatics 2011 27 4 541 547 10.1093/bioinformatics/btq702 2-s2.0-79951536020
57. Colijn C., Brandes A., Zucker J., Weiner B., Farhat M. R., Moody D. B., Murray M., Interpreting expression data with metabolic flux models: predicting Mycobacterium tuberculosis mycolic acid production. PLoS Computational Biology 2009 5 8 e1000489 10.1371/journal.pcbi.1000489 MR2545352 2-s2.0-70049110173
58. Burgard A. P., Pharkya P., Maranas C. D., Optknock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization. Biotechnology and Bioengineering 2003 84 6 647 657 10.1002/bit.10803 2-s2.0-0242487787
59. Pharkya P., Burgard A. P., Maranas C. D., OptStrain: a computational framework for redesign of microbial production systems. Genome Research 2004 14 11 2367 2376 10.1101/gr.2872004 2-s2.0-8744224466
60. Rocha I., Maia P., Evangelista P., Vilaça P., Soares S., Pinto J. P., Nielsen J., Patil K. R., Ferreira E. C., Rocha M., OptFlux: an open-source software platform for in silico metabolic engineering. BMC Systems Biology 2010 4 1, article 45 10.1186/1752-0509-4-45 2-s2.0-77950960250
61. Cvijovic M., Olivares-Hernandez R., Agren R., Dahr N., Vongsangnak W., Nookaew I., Patil K. R., Nielsen J., BioMet Toolbox: genome-wide analysis of metabolism. Nucleic Acids Research 2010 38 supplement 2 W144 W149 gkq404 10.1093/nar/gkq404 2-s2.0-77954291914
62. Yizhak K., Gabay O., Cohen H., Ruppin E., Model-based identification of drug targets that revert disrupted metabolism and its application to ageing. Nature Communications 2013 4 10.1038/ncomms3632 2-s2.0-84886670153
63. Jensen P. A., Lutz K. A., Papin J. A., TIGER: toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks. BMC Systems Biology 2011 5 1, article 147 10.1186/1752-0509-5-147 2-s2.0-80053175304
64. Gawand P., Hyland P., Ekins A., Martin V. J. J., Mahadevan R., Novel approach to engineer strains for simultaneous sugar utilization. Metabolic Engineering 2013 20 63 72 10.1016/j.ymben.2013.08.003 2-s2.0-84884962157
65. Kim J.-H., Block D. E., Mills D. A., Simultaneous consumption of pentose and hexose sugars: an optimal microbial phenotype for efficient fermentation of lignocellulosic biomass. Applied Microbiology and Biotechnology 2010 88 5 1077 1085 10.1007/s00253-010-2839-1 2-s2.0-78149408574
66. Lee S. K., Chou H., Ham T. S., Lee T. S., Keasling J. D., Metabolic engineering of microorganisms for biofuels production: from bugs to synthetic biology to fuels. Current Opinion in Biotechnology 2008 19 6 556 563 10.1016/j.copbio.2008.10.014 2-s2.0-57049098094
67. Courchesne N. M. D., Parisien A., Wang B., Lan C. Q., Enhancement of lipid production using biochemical, genetic and transcription factor engineering approaches. Journal of Biotechnology 2009 141 1-2 31 41 10.1016/j.jbiotec.2009.02.018 2-s2.0-64249131483
68. Yizhak K., Benyamini T., Liebermeister W., Ruppin E., Shlomi T., Integrating quantitative proteomics and metabolomics with a genome-scale metabolic network model. Bioinformatics 2010 26 12 i255 i260 btq183 10.1093/bioinformatics/btq183 2-s2.0-77954197778
69. Jamshidi N., Palsson B. Ø., Mass action stoichiometric simulation models: incorporating kinetics and regulation into stoichiometric models. Biophysical Journal 2010 98 2 175 185 10.1016/j.bpj.2009.09.064 2-s2.0-77049084742
70. Jerby L., Shlomi T., Ruppin E., Computational reconstruction of tissue-specific metabolic models: application to human liver metabolism. Molecular Systems Biology 2010 6, article 401 10.1038/msb.2010.56 2-s2.0-77956417789
71. Bochner B. R., Global phenotypic characterization of bacteria. FEMS Microbiology Reviews 2009 33 1 191 205 10.1111/j.1574-6976.2008.00149.x 2-s2.0-57649123534
72. Bochner B. R., New technologies to assess genotype-phenotype relationships. Nature Reviews Genetics 2003 4 4 309 314 10.1038/nrg1046 2-s2.0-0037379691
73. Vaas L. A. I., Sikorski J., Michael V., Göker M., Klenk H.-P., Visualization and curve-parameter estimation strategies for efficient exploration of phenotype microarray kinetics. PLoS ONE 2012 7 4 e34846 10.1371/journal.pone.0034846 2-s2.0-84859982600
74. Reed J. L., Patel T. R., Chen K. H., Joyce A. R., Applebee M. K., Herring C. D., Bui O. T., Knight E. M., Fong S. S., Palsson B. O., Systems approach to refining genome annotation. Proceedings of the National Academy of Sciences of the United States of America 2006 103 46 17480 17484 10.1073/pnas.0603364103 2-s2.0-33751226921
75. Medema M. H., van Raaphorst R., Takano E., Breitling R., Computational tools for the synthetic design of biochemical pathways. Nature Reviews Microbiology 2012 10 3 191 202 10.1038/nrmicro2717 2-s2.0-84857192122
76. Talebi A. F., Tohidfar M., Bagheri A., Manipulation of carbon flux into fatty acid biosynthesis pathway in Dunaliella salina using AccD and ME genes to enhance lipid content and to improve produced biodiesel quality. Biofuel Research Journal 2014 1 3 91 97
77. Andrianantoandro E., Basu S., Karig D. K., Weiss R., Synthetic biology: new engineering rules for an emerging discipline. Molecular Systems Biology 2006 2 1 msb4100073 10.1038/msb4100073 2-s2.0-33745454125
78. Benner S. A., Sismour A. M., Synthetic biology. Nature Reviews Genetics 2005 6 7 533 543 10.1038/nrg1637 2-s2.0-21344458620
79. Drubin D. A., Way J. C., Silver P. A., Designing biological systems. Genes and Development 2007 21 3 242 254 10.1101/gad.1507207 2-s2.0-33846949751
80. Marchisio M. A., Stelling J., Computational design of synthetic gene circuits with composable parts. Bioinformatics 2008 24 17 1903 1910 10.1093/bioinformatics/btn330 2-s2.0-50549103571
81. Lopez D., Casero D., Cokus S. J., Merchant S. S., Pellegrini M., Algal functional annotation tool: a web-based analysis suite to functionally interpret large gene lists using integrated annotation and expression data. BMC Bioinformatics 2011 12 1, article 282 10.1186/1471-2105-12-282 2-s2.0-79960158139
82. Chang R. L., Ghamsari L., Manichaikul A., Hom E. F. Y., Balaji S., Fu W., Shen Y., Hao T., Palsson B. Ø., Salehi-Ashtiani K., Papin J. A., Metabolic network reconstruction of Chlamydomonas offers insight into light-driven algal metabolism. Molecular Systems Biology 2011 7, article 518 10.1038/msb.2011.52 2-s2.0-80051537012
83. Boyle N. R., Morgan J. A., Flux balance analysis of primary metabolism in Chlamydomonas reinhardtii. BMC Systems Biology 2009 3, article 4 10.1186/1752-0509-3-4 2-s2.0-58849135386
84. Manichaikul A., Ghamsari L., Hom E. F. Y., Lin C., Murray R. R., Chang R. L., Balaji S., Hao T., Shen Y., Chavali A. K., Thiele I., Yang X., Fan C., Mello E., Hill D. E., Vidal M., Salehi-Ashtiani K., Papin J. A., Metabolic network analysis integrated with transcript verification for sequenced genomes. Nature Methods 2009 6 8 589 592 10.1038/nmeth.1348 2-s2.0-68349108021
85. de Oliveira Dal'Molin C. G., Quek L.-E., Palfreyman R. W., Nielsen L. K., AlgaGEM-a genome-scale metabolic reconstruction of algae based on the Chlamydomonas reinhardtii genome. BMC Genomics 2011 12 4, article S5 10.1186/1471-2164-12-S4-S5 2-s2.0-84255195408
86. May P., Christian J. O., Kempa S., Walther D., ChlamyCyc: an integrative systems biology database and web-portal for Chlamydomonas reinhardtii. BMC Genomics 2009 10, article 209 10.1186/1471-2164-10-209 2-s2.0-66349086716
87. Walhout A. J. M., Temple G. F., Brasch M. A., Hartley J. L., Lorson M. A., Van den Heuvel S., Vidal M., GATEWAY recombinational cloning: application to the cloning of large numbers of open reading frames or ORFeomes. Methods in Enzymology 2000 328 575 592 10.1016/S0076-6879(00)28419-X 2-s2.0-0033732564