Costas D Maranas

Summary

Affiliation: Pennsylvania State University
Country: USA

Publications

  1. pmc Rapid construction of metabolic models for a family of Cyanobacteria using a multiple source annotation workflow
    Thomas J Mueller
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA
    BMC Syst Biol 7:142. 2013
  2. pmc MetRxn: a knowledgebase of metabolites and reactions spanning metabolic models and databases
    Akhil Kumar
    Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
    BMC Bioinformatics 13:6. 2012
  3. pmc Computational design of Candida boidinii xylose reductase for altered cofactor specificity
    George A Khoury
    Department of Chemical Engineering, The Pennsylvania State University, University Park, 16802, USA
    Protein Sci 18:2125-38. 2009
  4. pmc Genome-scale gene/reaction essentiality and synthetic lethality analysis
    Patrick F Suthers
    Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
    Mol Syst Biol 5:301. 2009
  5. pmc Elucidation and structural analysis of conserved pools for genome-scale metabolic reconstructions
    Evgeni V Nikolaev
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Biophys J 88:37-49. 2005
  6. pmc OptForce: an optimization procedure for identifying all genetic manipulations leading to targeted overproductions
    Sridhar Ranganathan
    Huck Institutes of Life Sciences, The Pennsylvania State University, University Park, Pennsylvania, United States of America
    PLoS Comput Biol 6:e1000744. 2010
  7. pmc OptGraft: A computational procedure for transferring a binding site onto an existing protein scaffold
    Hossein Fazelinia
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Protein Sci 18:180-95. 2009
  8. pmc Reconstruction and comparison of the metabolic potential of cyanobacteria Cyanothece sp. ATCC 51142 and Synechocystis sp. PCC 6803
    Rajib Saha
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America
    PLoS ONE 7:e48285. 2012
  9. doi request reprint Improved computational performance of MFA using elementary metabolite units and flux coupling
    Patrick F Suthers
    Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
    Metab Eng 12:123-8. 2010
  10. pmc OptStrain: a computational framework for redesign of microbial production systems
    Priti Pharkya
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Genome Res 14:2367-76. 2004

Collaborators

  • Madhukar S Dasika
  • Patrick C Cirino
  • Evgeni V Nikolaev
  • Vinay Satish Kumar
  • Ye Li
  • John I Glass
  • Stephen Van Dien
  • James C Liao
  • Gennady Denisov
  • Christophe H Schilling
  • Patrick F Suthers
  • Ali R Zomorrodi
  • Sridhar Ranganathan
  • Manish C Saraf
  • Robert J Pantazes
  • Priti Pharkya
  • Anthony P Burgard
  • Hossein Fazelinia
  • Rajib Saha
  • Anupam Chowdhury
  • Thomas J Mueller
  • Matthew J Grisewood
  • Vinay Satish Kumar
  • Jonathan W Chin
  • Himadri B Pakrasi
  • Bertram M Berla
  • Akhil Kumar
  • Prabhasa Ravikirthi
  • George A Khoury
  • YoungJung Chang
  • Francisco G Vital-Lopez
  • Stephen J Benkovic
  • Nathanael P Gifford
  • Jimmy G Lafontaine Rivera
  • Michael J Janik
  • Alex T Verseput
  • Yanfen Fu
  • Ting Wei Tee
  • Jong Moon Yoon
  • Jacqueline V Shanks
  • Young J Chang
  • Alireza Zomorrodi
  • Reza Khankal
  • Caroline A Monroe
  • Farnaz Nowroozi
  • Jay D Keasling
  • Gregory L Moore
  • Nina M Goodey
  • Vania Y Cao
  • Antonios Armaou
  • Anshuman Gupta
  • Alexander R Horswill

Detail Information

Publications43

  1. pmc Rapid construction of metabolic models for a family of Cyanobacteria using a multiple source annotation workflow
    Thomas J Mueller
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA
    BMC Syst Biol 7:142. 2013
    ..The reconstruction of quality genome-scale metabolic models for organisms with limited annotation resources remains a challenging task...
  2. pmc MetRxn: a knowledgebase of metabolites and reactions spanning metabolic models and databases
    Akhil Kumar
    Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
    BMC Bioinformatics 13:6. 2012
    ..g., use of generic R-group or non-explicit specification of stereo-specificity)...
  3. pmc Computational design of Candida boidinii xylose reductase for altered cofactor specificity
    George A Khoury
    Department of Chemical Engineering, The Pennsylvania State University, University Park, 16802, USA
    Protein Sci 18:2125-38. 2009
    ..The remaining two variants (CbXR-RTT and CBXR-EQR) had dual cofactor specificity for both nicotinamide cofactors...
  4. pmc Genome-scale gene/reaction essentiality and synthetic lethality analysis
    Patrick F Suthers
    Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
    Mol Syst Biol 5:301. 2009
    ..By analyzing the functional classifications of the genes involved in synthetic lethals, we reveal surprising connections within and across clusters of orthologous group functional classifications...
  5. pmc Elucidation and structural analysis of conserved pools for genome-scale metabolic reconstructions
    Evgeni V Nikolaev
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Biophys J 88:37-49. 2005
    ..The developed approaches thus provide novel and versatile tools for elucidating coupling relationships between metabolite concentrations with implications in biotechnological and medical applications...
  6. pmc OptForce: an optimization procedure for identifying all genetic manipulations leading to targeted overproductions
    Sridhar Ranganathan
    Huck Institutes of Life Sciences, The Pennsylvania State University, University Park, Pennsylvania, United States of America
    PLoS Comput Biol 6:e1000744. 2010
    ..The method not only recapitulates existing engineering strategies but also reveals non-intuitive ones that boost succinate production by performing coordinated changes on pathways distant from the last steps of succinate synthesis...
  7. pmc OptGraft: A computational procedure for transferring a binding site onto an existing protein scaffold
    Hossein Fazelinia
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Protein Sci 18:180-95. 2009
    ....
  8. pmc Reconstruction and comparison of the metabolic potential of cyanobacteria Cyanothece sp. ATCC 51142 and Synechocystis sp. PCC 6803
    Rajib Saha
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America
    PLoS ONE 7:e48285. 2012
    ..Specific metabolic pathway differences between the two cyanobacteria alluding to different bio-production potentials are reflected in both models...
  9. doi request reprint Improved computational performance of MFA using elementary metabolite units and flux coupling
    Patrick F Suthers
    Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
    Metab Eng 12:123-8. 2010
    ..The observed computational savings reveal the rapid progress in performing MFA with increasingly larger isotope models with the ultimate goal of handling genome-scale models of metabolism...
  10. pmc OptStrain: a computational framework for redesign of microbial production systems
    Priti Pharkya
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Genome Res 14:2367-76. 2004
    ..In summary, OptStrain provides a useful tool to aid microbial strain design and, more importantly, it establishes an integrated framework to accommodate future modeling developments...
  11. doi request reprint Mathematical optimization applications in metabolic networks
    Ali R Zomorrodi
    Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA
    Metab Eng 14:672-86. 2012
    ..Overall, the methods reviewed in this paper highlight the diversity of queries, breadth of questions and complexity of redesigns that are amenable to mathematical optimization strategies...
  12. ncbi request reprint Exploring the overproduction of amino acids using the bilevel optimization framework OptKnock
    Priti Pharkya
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Biotechnol Bioeng 84:887-99. 2003
    ....
  13. ncbi request reprint Optimal protein library design using recombination or point mutations based on sequence-based scoring functions
    Robert J Pantazes
    Department of Chemical Engineering, The Pennsylvannia State University, University Park, PA 16802, USA
    Protein Eng Des Sel 20:361-73. 2007
    ..Computational benchmarking results demonstrate the efficacy of models OPTCOMB and OPTOLIGO to generate high scoring libraries of a prespecified size...
  14. pmc IPRO: an iterative computational protein library redesign and optimization procedure
    Manish C Saraf
    Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
    Biophys J 90:4167-80. 2006
    ..Computational results demonstrate that it is indeed feasible to improve the overall library quality as exemplified by binding energy scores through targeted mutations in the parental sequences...
  15. doi request reprint Optimization-driven identification of genetic perturbations accelerates the convergence of model parameters in ensemble modeling of metabolic networks
    Ali R Zomorrodi
    Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA
    Biotechnol J 8:1090-104. 2013
    ..Overall, this study provides a systematic way of optimally designing genetic perturbations for populating the ensemble of models with relevant model parameterizations. ..
  16. doi request reprint An integrated computational and experimental study for overproducing fatty acids in Escherichia coli
    Sridhar Ranganathan
    Huck Institutes of Life Sciences, Pennsylvania State University, University Park, PA, USA
    Metab Eng 14:687-704. 2012
    ..These results highlight the benefit of using computational strain design and flux analysis tools in the design of recombinant strains of E. coli to produce free fatty acids...
  17. ncbi request reprint A computational procedure for optimal engineering interventions using kinetic models of metabolism
    Francisco G Vital-Lopez
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Biotechnol Prog 22:1507-17. 2006
    ..coli for serine overproduction. The proposed computational procedure is a general approach that can be applied to any metabolic system for which a kinetic description is provided...
  18. doi request reprint Identification of optimal measurement sets for complete flux elucidation in metabolic flux analysis experiments
    YoungJung Chang
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Biotechnol Bioeng 100:1039-49. 2008
    ..coli isotopomer mapping model with more than 17,000 isotopomers. A number of additional measurements are identified leading to maximum flux elucidation in an amorphadiene producing E. coli strain...
  19. pmc Extending Iterative Protein Redesign and Optimization (IPRO) in protein library design for ligand specificity
    Hossein Fazelinia
    Department of Chemical Engineering, 112A Fenske Laboratory, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Biophys J 92:2120-30. 2007
    ..Pinpointing a small set of mutations within the binding pocket greatly improves the difference in binding energies between targeted and decoy ligands, even when they are very similar...
  20. pmc OptCircuit: an optimization based method for computational design of genetic circuits
    Madhukar S Dasika
    Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
    BMC Syst Biol 2:24. 2008
    ..This is because of the incomplete description of component interactions compounded by the fact that the number of ways in which one can chose and interconnect components, increases exponentially with the number of components...
  21. doi request reprint Analysis of NADPH supply during xylitol production by engineered Escherichia coli
    Jonathan W Chin
    Department of Chemical Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Biotechnol Bioeng 102:209-20. 2009
    ....
  22. ncbi request reprint Design of combinatorial protein libraries of optimal size
    Manish C Saraf
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16082, USA
    Proteins 60:769-77. 2005
    ..Results reveal that the best library designs typically involve complex tiling patterns of parental segments of unequal size hard to infer without relying on computational means...
  23. pmc Optimization based automated curation of metabolic reconstructions
    Vinay Satish Kumar
    Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, PA 16802, USA
    BMC Bioinformatics 8:212. 2007
    ..A key challenge in the automated generation of genome-scale reconstructions is the elucidation of these gaps and the subsequent generation of hypotheses to bridge them...
  24. pmc Metabolic flux elucidation for large-scale models using 13C labeled isotopes
    Patrick F Suthers
    Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
    Metab Eng 9:387-405. 2007
    ..Finally, we discuss the effect of reducing the model, as well as shed light onto the customization of the developed computational framework to other systems...
  25. pmc GrowMatch: an automated method for reconciling in silico/in vivo growth predictions
    Vinay Satish Kumar
    Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America
    PLoS Comput Biol 5:e1000308. 2009
    ..In addition, GrowMatch can be used during the construction phase of new, as opposed to existing, genome-scale metabolic models, leading to more expedient and accurate reconstructions...
  26. pmc A genome-scale metabolic reconstruction of Mycoplasma genitalium, iPS189
    Patrick F Suthers
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America
    PLoS Comput Biol 5:e1000285. 2009
    ..genitalium. Approaches and tools described herein provide a roadmap for the automated construction of in silico metabolic models of other organisms...
  27. ncbi request reprint Using a residue clash map to functionally characterize protein recombination hybrids
    Manish C Saraf
    Department of Chemical Engineering, The Pennsylvania State University, 112 Fenske Laboratory, University Park, PA 16802, USA
    Protein Eng 16:1025-34. 2003
    ..This suggests that residue clash maps can provide quantitative guidelines for the placement of crossovers in the design of protein recombination experiments...
  28. doi request reprint Construction of an E. Coli genome-scale atom mapping model for MFA calculations
    Prabhasa Ravikirthi
    Department of Cell and Developmental Biology, The Pennsylvania State University, University Park, Pennsylvania, USA
    Biotechnol Bioeng 108:1372-82. 2011
    ..An EMU representation of imPR90068 is also constructed and made available...
  29. doi request reprint Recent advances in computational protein design
    Robert J Pantazes
    The Pennsylvania State University, Department of Chemical Engineering, 112 Fenske Lab, University Park, PA 16802, USA
    Curr Opin Struct Biol 21:467-72. 2011
    ..Studies that successfully meet all these criteria are beginning to emerge including the design of an O(2)-binding protein and a novel enzyme that catalyzes a Diels-Alder reaction...
  30. pmc OptZyme: computational enzyme redesign using transition state analogues
    Matthew J Grisewood
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America
    PLoS ONE 8:e75358. 2013
    ..Mutants predicted to enhance the activity for para-nitrophenyl- β, D-galactoside directly or indirectly create hydrogen bonds with the altered sugar ring conformation or its substituents, namely H162S, L361G, W549R, and N550S. ..
  31. pmc A computational framework for the topological analysis and targeted disruption of signal transduction networks
    Madhukar S Dasika
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Biophys J 91:382-98. 2006
    ..Overall the proposed computational frameworks can help elucidate input/output relationships of signaling networks and help to guide the systematic design of interference strategies...
  32. pmc FamClash: a method for ranking the activity of engineered enzymes
    Manish C Saraf
    Department of Chemistry, 414 Wartik Laboratory, Pennsylvania State University, University Park, PA 16802, USA
    Proc Natl Acad Sci U S A 101:4142-7. 2004
    ..Comparisons of the predicted clash map as a function of crossover position revealed good agreement with activity data, reproducing the observed V shape and matching the location of a local peak in activity...
  33. doi request reprint Microbial 1-butanol production: Identification of non-native production routes and in silico engineering interventions
    Sridhar Ranganathan
    Huck Institutes of Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA
    Biotechnol J 5:716-25. 2010
    ....
  34. ncbi request reprint DEMSIM: a discrete event based mechanistic simulation platform for gene expression and regulation dynamics
    Madhukar S Dasika
    Department of Chemical Engineering, The Pennsylvania State University, 112A Fenske Laboratory, University Park, PA 16802, USA
    J Theor Biol 232:55-69. 2005
    ..Overall, the obtained results highlight the effectiveness of DEMSIM at describing the underlying biological processes involved in gene regulation for querying alternative regulatory hypotheses...
  35. pmc Zea mays iRS1563: a comprehensive genome-scale metabolic reconstruction of maize metabolism
    Rajib Saha
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America
    PLoS ONE 6:e21784. 2011
    ..e., bm1 and bm3). The developed model corresponds to the largest and more complete to-date effort at cataloguing metabolism for a plant species...
  36. doi request reprint k-OptForce: integrating kinetics with flux balance analysis for strain design
    Anupam Chowdhury
    Department of Chemical Engineering, Pennsylvania State University, University Park, Pennsylvania, United States of America
    PLoS Comput Biol 10:e1003487. 2014
    ..This study paves the way for the integrated analysis of kinetic and stoichiometric models and enables elucidating system-wide metabolic interventions while capturing regulatory and kinetic effects. ..
  37. pmc OptCom: a multi-level optimization framework for the metabolic modeling and analysis of microbial communities
    Ali R Zomorrodi
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA
    PLoS Comput Biol 8:e1002363. 2012
    ....
  38. pmc Metabolic reconstruction of the archaeon methanogen Methanosarcina Acetivorans
    Vinay Satish Kumar
    Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
    BMC Syst Biol 5:28. 2011
    ..acetivorans. This process relies on previously developed computational tools developed in our group to correct growth prediction inconsistencies with in vivo data sets and rectify topological inconsistencies in the model...
  39. pmc Flux coupling analysis of genome-scale metabolic network reconstructions
    Anthony P Burgard
    Department of Chemical Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Genome Res 14:301-12. 2004
    ..The FCF approach thus provides a novel and versatile tool for aiding metabolic reconstructions and guiding genetic manipulations...
  40. ncbi request reprint An optimization framework for identifying reaction activation/inhibition or elimination candidates for overproduction in microbial systems
    Priti Pharkya
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Metab Eng 8:1-13. 2006
    ..The OptReg framework is a versatile tool for strain design which allows for a broad array of genetic manipulations...
  41. doi request reprint Orchestrating hi-fi annotations
    Patrick F Suthers
    Pennsylvania State University, Department of Chemical Engineering, University Park, PA, USA
    Nat Chem Biol 8:810-1. 2012
    ....
  42. ncbi request reprint Optknock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization
    Anthony P Burgard
    Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Biotechnol Bioeng 84:647-57. 2003
    ..Finally, the OptKnock procedure, by coupling biomass formation with chemical production, hints at a growth selection/adaptation system for indirectly evolving overproducing mutants...
  43. pmc Improving the iMM904 S. cerevisiae metabolic model using essentiality and synthetic lethality data
    Ali R Zomorrodi
    Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
    BMC Syst Biol 4:178. 2010
    ..coli model (i.e., iAF1260). This is manifested by its significantly lower specificity in predicting the outcome of grow/no grow experiments in comparison to the E. coli model...