Abstract is: Bernhard Ørn Palsson is the Galletti Professor of Bioengineering and an adjunct professor of Medicine at the University of California, San Diego.
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| P1280 | CONOR.SI ID | 103964003 |
| P2456 | DBLP author ID | 55/3828 |
| P6178 | Dimensions author ID | 011260472057.92 |
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| P1960 | Google Scholar author ID | lhS3Su4AAAAJ |
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| P244 | Library of Congress authority ID | nb98086172 |
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| P8189 | National Library of Israel J9U ID | 987007577047005171 |
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| P691 | NL CR AUT ID | xx0201439 |
| P1015 | NORAF ID | 3086454 |
| P1207 | NUKAT ID | n2004027481 |
| P496 | ORCID iD | 0000-0003-2357-6785 |
| P1153 | Scopus author ID | 8108272000 |
| P906 | SELIBR ID | 319255 |
| P3987 | SHARE Catalogue author ID | 501629 |
| P11686 | University of Barcelona authority ID | 981058520091806706 |
| P1580 | University of Barcelona authority ID (former scheme) | a1129149 |
| P214 | VIAF ID | 37091465 |
| P10832 | WorldCat Entities ID | E39PBJjxvpCqTDDTgXbXkwkhpP |
| P1416 | affiliation | DTU Biosustain | Q42751697 |
| P166 | award received | Fulbright Scholarship | Q253936 |
| Fellow of the American Association for the Advancement of Science | Q5442484 | ||
| P27 | country of citizenship | United States of America | Q30 |
| P184 | doctoral advisor | Edwin N. Lightfoot | Q5346687 |
| P185 | doctoral student | Jay Keasling | Q1684333 |
| P69 | educated at | University of Wisconsin–Madison | Q838330 |
| P108 | employer | University of Michigan | Q230492 |
| University of California, San Diego | Q622664 | ||
| P101 | field of work | bioengineering | Q580689 |
| tissue engineering | Q1540285 | ||
| P735 | given name | Bernhard | Q221978 |
| Bernhard | Q221978 | ||
| P1412 | languages spoken, written or signed | English | Q1860 |
| P463 | member of | National Academy of Engineering | Q1493021 |
| P106 | occupation | university teacher | Q1622272 |
| bioinformatician | Q2904006 | ||
| P21 | sex or gender | male | Q6581097 |
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| Q35135595 | Metabolic pathways in the post-genome era. |
| Q28469320 | Metabolic reconstruction and modeling of nitrogen fixation in Rhizobium etli |
| Q37601038 | Metabolic systems biology |
| Q33235593 | Metabolite coupling in genome-scale metabolic networks |
| Q44094042 | Metabolomic analysis of platelets during storage: a comparison between apheresis- and buffy coat-derived platelet concentrates. |
| Q48334173 | Metabolomics comparison of red cells stored in four additive solutions reveals differences in citrate anticoagulant permeability and metabolism |
| Q58693878 | Metagenomics-Based, Strain-Level Analysis of Escherichia coli From a Time-Series of Microbiome Samples From a Crohn's Disease Patient |
| Q35176401 | Microbial laboratory evolution in the era of genome-scale science |
| Q36919216 | Microbial regulatory and metabolic networks. |
| Q46403197 | Microbiology. Topping off a multiscale balancing act. |
| Q64101958 | Minimal cells, maximal knowledge |
| Q34986572 | Minimal metabolic pathway structure is consistent with associated biomolecular interactions |
| Q35031478 | Model-driven discovery of underground metabolic functions in Escherichia coli |
| Q35073789 | Model-driven evaluation of the production potential for growth-coupled products of Escherichia coli |
| Q34317619 | Model-driven multi-omic data analysis elucidates metabolic immunomodulators of macrophage activation |
| Q46101177 | Modeling Method for Increased Precision and Scope of Directly Measurable Fluxes at a Genome-Scale |
| Q59789922 | Modeling genome-wide enzyme evolution predicts strong epistasis underlying catalytic turnover rates |
| Q35193476 | Modeling methanogenesis with a genome-scale metabolic reconstruction of Methanosarcina barkeri |
| Q47556883 | Modeling the multi-scale mechanisms of macromolecular resource allocation. |
| Q39430006 | Monitoring metabolites consumption and secretion in cultured cells using ultra-performance liquid chromatography quadrupole-time of flight mass spectrometry (UPLC-Q-ToF-MS). |
| Q47417801 | Monte Carlo sampling can be used to determine the size and shape of the steady-state flux space |
| Q31139124 | Multi-omic data integration enables discovery of hidden biological regularities |
| Q41410982 | Multi-omics Quantification of Species Variation of Escherichia coli Links Molecular Features with Strain Phenotypes |
| Q41486364 | Multidimensional analytical approach based on UHPLC-UV-ion mobility-MS for the screening of natural pigments |
| Q90579714 | Multiple Optimal Phenotypes Overcome Redox and Glycolytic Intermediate Metabolite Imbalances in Escherichia coli pgi Knockout Evolutions |
| Q28710105 | Multiple-omic data analysis of Klebsiella pneumoniae MGH 78578 reveals its transcriptional architecture and regulatory features |
| Q92093223 | Multiplex secretome engineering enhances recombinant protein production and purity |
| Q34429661 | Multiscale modeling of metabolism and macromolecular synthesis in E. coli and its application to the evolution of codon usage |
| Q37193094 | Multispecific drug transporter Slc22a8 (Oat3) regulates multiple metabolic and signaling pathways |
| Q31062725 | Murine Sca-1(+)/Lin(-) cells and human KG1a cells exhibit multiple pseudopod morphologies during migration |
| Q34296873 | Network context and selection in the evolution to enzyme specificity. |
| Q37526602 | Network reconstruction of platelet metabolism identifies metabolic signature for aspirin resistance |
| Q28212164 | Network-based analysis of metabolic regulation in the human red blood cell |
| Q81798711 | Network-based prediction of human tissue-specific metabolism |
| Q58797064 | Network-level allosteric effects are elucidated by detailing how ligand-binding events modulate utilization of catalytic potentials |
| Q33236264 | Network-level analysis of metabolic regulation in the human red blood cell using random sampling and singular value decomposition |
| Q38312915 | Next-generation genome-scale models for metabolic engineering. |
| Q33642720 | Omic data from evolved E. coli are consistent with computed optimal growth from genome-scale models |
| Q46774634 | Optimizing genome-scale network reconstructions |
| Q33235934 | Optoinjection for efficient targeted delivery of a broad range of compounds and macromolecules into diverse cell types. |
| Q90941322 | OxyR Is a Convergent Target for Mutations Acquired during Adaptation to Oxidative Stress-Prone Metabolic States |
| Q46204807 | PCR-based tandem epitope tagging system for Escherichia coli genome engineering |
| Q125340985 | Pan-Genome Analysis of Transcriptional Regulation in Six Salmonella enterica Serovar Typhimurium Strains Reveals Their Different Regulatory Structures |
| Q42122006 | Parallel adaptive evolution cultures of Escherichia coli lead to convergent growth phenotypes with different gene expression states |
| Q39803501 | Personalized Whole-Cell Kinetic Models of Metabolism for Discovery in Genomics and Pharmacodynamics |
| Q30968128 | Pharmacogenomic and clinical data link non-pharmacokinetic metabolic dysregulation to drug side effect pathogenesis |
| Q43763379 | Predicting gene essentiality using genome-scale in silico models |
| Q34144792 | Predicting outcomes of steady-state ¹³C isotope tracing experiments using Monte Carlo sampling |
| Q93139421 | Predicting the metabolic capabilities of Synechococcus elongatus PCC 7942 adapted to different light regimes |
| Q30951388 | Prediction of intracellular metabolic states from extracellular metabolomic data |
| Q92309863 | Primary transcriptome and translatome analysis determines transcriptional and translational regulatory elements encoded in the Streptomyces clavuligerus genome |
| Q31142835 | Principles of proteome allocation are revealed using proteomic data and genome-scale models |
| Q84324563 | Probing the basis for genotype-phenotype relationships |
| Q46525276 | Proceedings of the Food and Drug Administration's public workshop on new red blood cell product regulatory science 2016. |
| Q92058978 | Profiling the effect of nafcillin on HA-MRSA D712 using bacteriological and physiological media |
| Q37169863 | Proteomic analysis of Chinese hamster ovary cells |
| Q62784502 | Pseudogene repair driven by selection pressure applied in experimental evolution |
| Q91709397 | Publisher Correction: MEMOTE for standardized genome-scale metabolic model testing |
| Q30151952 | Quantification and Classification of E. coli Proteome Utilization and Unused Protein Costs across Environments |
| Q50135305 | Quantitative -omic data empowers bottom-up systems biology |
| Q38762776 | Quantitative feature extraction from the Chinese hamster ovary bioprocess bibliome using a novel meta-analysis workflow |
| Q28246991 | Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0 |
| Q42516826 | Quantitative time-course metabolomics in human red blood cells reveal the temperature dependence of human metabolic networks |
| Q34377515 | RNA polymerase mutants found through adaptive evolution reprogram Escherichia coli for optimal growth in minimal media |
| Q49850956 | Recon3D enables a three-dimensional view of gene variation in human metabolism. |
| Q30882253 | Reconciling Gene Expression Data With Known Genome-Scale Regulatory Network Structures |
| Q30592724 | Reconciling a Salmonella enterica metabolic model with experimental data confirms that overexpression of the glyoxylate shunt can rescue a lethal ppc deletion mutant |
| Q46083927 | Reconstructing metabolic flux vectors from extreme pathways: defining the alpha-spectrum |
| Q99594982 | Reconstructing organisms in silico: genome-scale models and their emerging applications |
| Q51900913 | Reconstruction and Use of Microbial Metabolic Networks: the Core Escherichia coli Metabolic Model as an Educational Guide. |
| Q90480137 | Reconstruction and Validation of a Genome-Scale Metabolic Model of Streptococcus oralis (iCJ415), a Human Commensal and Opportunistic Pathogen |
| Q30939059 | Reconstruction and functional characterization of the human mitochondrial metabolic network based on proteomic and biochemical data |
| Q34253865 | Reconstruction and modeling protein translocation and compartmentalization in Escherichia coli at the genome-scale |
| Q35574107 | Reconstruction and validation of Saccharomyces cerevisiae iND750, a fully compartmentalized genome-scale metabolic model |
| Q42777265 | Reconstruction annotation jamborees: a community approach to systems biology |
| Q34385115 | Reconstruction of cellular signalling networks and analysis of their properties |
| Q35753262 | Reconstruction of microbial transcriptional regulatory networks |
| Q97522724 | Redefining fundamental concepts of transcription initiation in bacteria |
| Q60044413 | Reframing gene essentiality in terms of adaptive flexibility |
| Q37591109 | Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression |
| Q96949886 | Revealing 29 sets of independently modulated genes in Staphylococcus aureus, their regulators, and role in key physiological response |
| Q33708425 | Revealing genome-scale transcriptional regulatory landscape of OmpR highlights its expanded regulatory roles under osmotic stress in Escherichia coli K-12 MG1655 |
| Q58615071 | Revealing key determinants of clonal variation in transgene expression in recombinant CHO cells using targeted genome editing |
| Q112715428 | RiboRid: A low cost, advanced, and ultra-efficient method to remove ribosomal RNA for bacterial transcriptomics |
| Q98729427 | SBML Level 3: an extensible format for the exchange and reuse of biological models |
| Q35802135 | SBMLsqueezer 2: context-sensitive creation of kinetic equations in biochemical networks |
| Q92986935 | STATR: A simple analysis pipeline of Ribo-Seq in bacteria |
| Q37087145 | Saccharomyces cerevisiae phenotypes can be predicted by using constraint-based analysis of a genome-scale reconstructed metabolic network |
| Q36880073 | Salmonella modulates metabolism during growth under conditions that induce expression of virulence genes |
| Q44526702 | Scalable method to determine mutations that occur during adaptive evolution of Escherichia coli |
| Q30476280 | Sensitive and accurate identification of protein-DNA binding events in ChIP-chip assays using higher order derivative analysis |
| Q46484047 | Sequence-based analysis of metabolic demands for protein synthesis in prokaryotes |
| Q27818844 | Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking |
| Q93021098 | Strain-Specific Metabolic Requirements Revealed by a Defined Minimal Medium for Systems Analyses of Staphylococcus aureus |
| Q34085173 | Structural and operational complexity of the Geobacter sulfurreducens genome. |
| Q37184562 | Structural systems biology evaluation of metabolic thermotolerance in Escherichia coli |
| Q91771704 | Structure of galactarate dehydratase, a new fold in an enolase involved in bacterial fitness after antibiotic treatment |
| Q38034106 | Studying Salmonellae and Yersiniae host-pathogen interactions using integrated 'omics and modeling |
| Q93175937 | Sugar-stimulated CO2 sequestration by the green microalga Chlorella vulgaris |
| Q92043920 | Synthetic Biology Tools for Novel Secondary Metabolite Discovery in Streptomyces |
| Q98303221 | Synthetic cross-phyla gene replacement and evolutionary assimilation of major enzymes |
| Q36098282 | Systematic condition-dependent annotation of metabolic genes |
| Q91101739 | Systematic discovery of uncharacterized transcription factors in Escherichia coli K-12 MG1655 |
| Q35058632 | Systematizing the generation of missing metabolic knowledge |
| Q44538085 | Systemic metabolic reactions are obtained by singular value decomposition of genome-scale stoichiometric matrices |
| Q92912360 | Systems Biology and Pangenome of Salmonella O-Antigens |
| Q40163676 | Systems analysis of energy metabolism elucidates the affected respiratory chain complex in Leigh's syndrome |
| Q57175579 | Systems analysis of metabolism in platelet concentrates during storage in platelet additive solution |
| Q35768707 | Systems approach to refining genome annotation |
| Q47638844 | Systems assessment of transcriptional regulation on central carbon metabolism by Cra and CRP. |
| Q37604410 | Systems biology analysis of drivers underlying hallmarks of cancer cell metabolism |
| Q100750140 | Systems biology analysis of the Clostridioides difficile core-genome contextualizes microenvironmental evolutionary pressures leading to genotypic and phenotypic divergence |
| Q38159855 | Systems biology and biotechnology of Streptomyces species for the production of secondary metabolites |
| Q36578151 | Systems biology as a foundation for genome-scale synthetic biology |
| Q30986341 | Systems biology definition of the core proteome of metabolism and expression is consistent with high-throughput data. |
| Q36527343 | Systems biology of SNPs |
| Q42668216 | Systems biology of stored blood cells: can it help to extend the expiration date? |
| Q36419834 | Systems biology of the human red blood cell |
| Q24672160 | Systems biology of the structural proteome |
| Q92149993 | Systems-level analysis of NalD mutation, a recurrent driver of rapid drug resistance in acute Pseudomonas aeruginosa infection |
| Q35025547 | Technologies and approaches to elucidate and model the virulence program of salmonella |
| Q89011264 | Temperature-Dependent Estimation of Gibbs Energies Using an Updated Group-Contribution Method |
| Q21145722 | The COMBREX project: design, methodology, and initial results |
| Q91665941 | The Escherichia coli transcriptome mostly consists of independently regulated modules |
| Q40288125 | The JAK-STAT signaling network in the human B-cell: an extreme signaling pathway analysis |
| Q35174764 | The PurR regulon in Escherichia coli K-12 MG1655. |
| Q63214131 | The Staphylococcus aureus Two-Component System AgrAC Displays Four Distinct Genomic Arrangements That Delineate Genomic Virulence Factor Signatures |
| Q54976595 | The Staphylococcus aureus Two-Component System AgrAC Displays Four Distinct Genomic Arrangements That Delineate Genomic Virulence Factor Signatures. |
| Q90290574 | The Transcription Unit Architecture of Streptomyces lividans TK24 |
| Q43533034 | The aldehyde dehydrogenase, AldA, is essential for L-1,2-propanediol utilization in laboratory-evolved Escherichia coli. |
| Q35237052 | The architecture of ArgR-DNA complexes at the genome-scale in Escherichia coli |
| Q37739662 | The biomass objective function |
| Q33728907 | The challenges of integrating multi-omic data sets |
| Q34181787 | The convex basis of the left null space of the stoichiometric matrix leads to the definition of metabolically meaningful pools |
| Q35001424 | The development of a fully-integrated immune response model (FIRM) simulator of the immune response through integration of multiple subset models. |
| Q82241869 | The econometrics of evolution |
| Q92544990 | The emergence of adaptive laboratory evolution as an efficient tool for biological discovery and industrial biotechnology |
| Q51602866 | The evolution of molecular biology into systems biology. |
| Q35188192 | The genomic sequence of the Chinese hamster ovary (CHO)-K1 cell line |
| Q34244913 | The global transcriptional regulatory network for metabolism in Escherichia coli exhibits few dominant functional states. |
| Q34785166 | The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli |
| Q34036307 | The human metabolic reconstruction Recon 1 directs hypotheses of novel human metabolic functions |
| Q31032864 | The model organism as a system: integrating 'omics' data sets |
| Q114871791 | The quantitative metabolome is shaped by abiotic constraints |
| Q37320317 | The transcription unit architecture of the Escherichia coli genome |
| Q64255320 | The y-ome defines the 35% of Escherichia coli genes that lack experimental evidence of function |
| Q57476782 | Thermodynamic favorability and pathway yield as evolutionary tradeoffs in biosynthetic pathway choice |
| Q46138830 | Thermosensitivity of growth is determined by chaperone-mediated proteome reallocation |
| Q35109629 | Thirteen years of building constraint-based in silico models of Escherichia coli |
| Q89701303 | Thirty complete Streptomyces genome sequences for mining novel secondary metabolite biosynthetic gene clusters |
| Q33318131 | Three factors underlying incorrect in silico predictions of essential metabolic genes |
| Q33707860 | Three-dimensional structural view of the central metabolic network of Thermotoga maritima |
| Q28473553 | Top-down analysis of temporal hierarchy in biochemical reaction networks |
| Q46889284 | Topological analysis of mass-balanced signaling networks: a framework to obtain network properties including crosstalk |
| Q48364480 | Topological and kinetic determinants of the modal matrices of dynamic models of metabolism |
| Q36695097 | Toward whole cell modeling and simulation: comprehensive functional genomics through the constraint-based approach |
| Q37696969 | Towards genome-scale signalling network reconstructions |
| Q36371202 | Towards multidimensional genome annotation |
| Q34128076 | Transcriptional regulation in constraints-based metabolic models of Escherichia coli |
| Q46963426 | Transcriptional regulation of the fad regulon genes of Escherichia coli by ArcA. |
| Q94569499 | Transcriptome and translatome profiles of Streptomyces species in different growth phases |
| Q80833903 | Two-dimensional annotation of genomes |
| Q50502137 | UPLC-UV-MS(E) analysis for quantification and identification of major carotenoid and chlorophyll species in algae. |
| Q37326025 | Understanding human metabolic physiology: a genome-to-systems approach |
| Q34187246 | Uniform sampling of steady-state flux spaces: means to design experiments and to interpret enzymopathies. |
| Q114870402 | Unraveling the functions of uncharacterized transcription factors in Escherichia coli using ChIP-exo |
| Q24812778 | Untangling the web of functional and physical interactions in yeast |
| Q52676732 | Updated and standardized genome-scale reconstruction of Mycobacterium tuberculosis H37Rv, iEK1011, simulates flux states indicative of physiological conditions. |
| Q34747829 | Use of adaptive laboratory evolution to discover key mutations enabling rapid growth of Escherichia coli K-12 MG1655 on glucose minimal medium |
| Q37305068 | Use of randomized sampling for analysis of metabolic networks |
| Q28085366 | Using Genome-scale Models to Predict Biological Capabilities |
| Q33437242 | Using in silico models to simulate dual perturbation experiments: procedure development and interpretation of outcomes |
| Q33201572 | Using metabolic flux data to further constrain the metabolic solution space and predict internal flux patterns: the Escherichia coli spectrum |
| Q35927261 | What Makes a Bacterial Species Pathogenic?:Comparative Genomic Analysis of the Genus Leptospira |
| Q36929022 | What do cells actually want? |
| Q28275348 | What is flux balance analysis? |
| Q28817609 | Whole-Genome Sequencing of Invasion-Resistant Cells Identifies Laminin α2 as a Host Factor for Bacterial Invasion |
| Q42676209 | Whole-genome resequencing of Escherichia coli K-12 MG1655 undergoing short-term laboratory evolution in lactate minimal media reveals flexible selection of adaptive mutations |
| Q33958875 | iAB-RBC-283: A proteomically derived knowledge-base of erythrocyte metabolism that can be used to simulate its physiological and patho-physiological states |
| Q52564615 | iCN718, an Updated and Improved Genome-Scale Metabolic Network Reconstruction of Acinetobacter baumannii AYE. |
| Q46333912 | iML1515, a knowledgebase that computes Escherichia coli traits. |
| Q34189294 | k-Cone analysis: determining all candidate values for kinetic parameters on a network scale |
| Q111149889 | proChIPdb: a chromatin immunoprecipitation database for prokaryotic organisms |
| Q36141892 | solveME: fast and reliable solution of nonlinear ME models |
| Q49999902 | ssbio: A Python Framework for Structural Systems Biology |
| Q1684333 | Jay Keasling | doctoral advisor | P184 |
| Q5346687 | Edwin N. Lightfoot | doctoral student | P185 |
| Bernhard Palsson | wikipedia |
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