What is he best known for?
The fields of study he is best known for:
His primary areas of investigation include Biochemistry, Yeast, Saccharomyces cerevisiae, Corynebacterium glutamicum and Gene.
He interconnects Strain and Bacteria in the investigation of issues within Biochemistry.
His Yeast research incorporates elements of Fermentation, Food science, Fed-batch culture, Fuzzy logic and Lactic acid.
He has researched Saccharomyces cerevisiae in several fields, including Growth inhibition, Cell growth, Glutathione, Cysteine and Adaptation.
His Corynebacterium glutamicum study combines topics in areas such as Phosphoenolpyruvate carboxylase, Overproduction, Metabolic flux analysis and Pyruvate carboxylase.
His Gene study results in a more complete grasp of Genetics.
His most cited work include:
- Comprehensive phenotypic analysis for identification of genes affecting growth under ethanol stress in Saccharomyces cerevisiae. (179 citations)
- Identification of target genes conferring ethanol stress tolerance to Saccharomyces cerevisiae based on DNA microarray data analysis. (167 citations)
- Solar cell device (142 citations)
What are the main themes of his work throughout his whole career to date?
Hiroshi Shimizu spends much of his time researching Biochemistry, Saccharomyces cerevisiae, Yeast, Fermentation and Metabolic engineering.
His Strain research extends to the thematically linked field of Biochemistry.
His Saccharomyces cerevisiae research incorporates themes from DNA microarray and Trehalose.
His studies link Cell growth with Yeast.
His Fermentation study is concerned with the larger field of Food science.
His work carried out in the field of Metabolic flux analysis brings together such families of science as Citric acid cycle and Pentose phosphate pathway.
He most often published in these fields:
- Biochemistry (30.77%)
- Saccharomyces cerevisiae (13.53%)
- Yeast (11.41%)
What were the highlights of his more recent work (between 2013-2021)?
- Biochemistry (30.77%)
- Flux (8.22%)
- Metabolic engineering (10.88%)
In recent papers he was focusing on the following fields of study:
Hiroshi Shimizu mostly deals with Biochemistry, Flux, Metabolic engineering, Metabolism and Metabolic flux analysis.
His research on Biochemistry frequently links to adjacent areas such as Strain.
As a member of one scientific family, Hiroshi Shimizu mostly works in the field of Flux, focusing on Cofactor and, on occasion, Biophysics.
His Metabolic engineering research includes themes of Amino acid, Corynebacterium glutamicum, Dehydrogenase and Flux balance analysis, Computational biology.
His work deals with themes such as Oxidative phosphorylation, Citrate synthase and Mass spectrometry, which intersect with Metabolic flux analysis.
The research on Yeast and Gene is part of his Saccharomyces cerevisiae project.
Between 2013 and 2021, his most popular works were:
- OpenMebius: An Open Source Software for Isotopically Nonstationary 13C-Based Metabolic Flux Analysis (66 citations)
- Integrated metabolic flux and omics analysis of Synechocystis sp. PCC 6803 under mixotrophic and photoheterotrophic conditions (59 citations)
- Recent advances in amino acid production by microbial cells. (56 citations)
In his most recent research, the most cited papers focused on:
His primary scientific interests are in Biochemistry, Metabolic engineering, Metabolic flux analysis, Metabolism and Flux.
Biochemistry connects with themes related to Strain in his study.
His Metabolic engineering study combines topics from a wide range of disciplines, such as Amino acid, Corynebacterium glutamicum, Dehydrogenase, Flux balance analysis and NAD+ kinase.
His study looks at the intersection of Metabolic flux analysis and topics like Pentose phosphate pathway with Carbon fixation, Oxidative phosphorylation and Cell biology.
His research integrates issues of Carbon source, Computational biology, Metabolic network and Mass spectrometry in his study of Flux.
His Saccharomyces cerevisiae study contributes to a more complete understanding of Gene.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
