What is he best known for?
The fields of study he is best known for:
- Gene
- Artificial intelligence
- DNA
Guy-Bart Stan mainly focuses on Synthetic biology, Control theory, Systems biology, Bioinformatics and Computational biology.
The concepts of his Synthetic biology study are interwoven with issues in Metabolic engineering, Biochemical engineering, Psychological repression, Biotechnology and Software.
Control theory and System identification are commonly linked in his work.
His Systems biology study combines topics in areas such as Resolution, DNA metabolism and Systems engineering.
His studies in Bioinformatics integrate themes in fields like Biological system and Expression.
Guy-Bart Stan has included themes like Gene expression, CRISPR and Microbiology in his Computational biology study.
His most cited work include:
- Analysis of Interconnected Oscillators by Dissipativity Theory (269 citations)
- Comparison of different impulse response measurement techniques (181 citations)
- The Synthetic Biology Open Language (SBOL) provides a community standard for communicating designs in synthetic biology (176 citations)
What are the main themes of his work throughout his whole career to date?
Guy-Bart Stan focuses on Synthetic biology, Control theory, Computational biology, Mathematical optimization and Nonlinear system.
His Synthetic biology research includes themes of Natural language processing, Data model, Systems biology, Artificial intelligence and Operon.
His study focuses on the intersection of Operon and fields such as Biological system with connections in the field of Bioinformatics.
His Control theory research integrates issues from Gene regulatory network and Reinforcement learning.
His study looks at the intersection of Computational biology and topics like Gene expression with Protein biosynthesis.
His work is dedicated to discovering how Nonlinear system, Algorithm are connected with Structure, System identification and Noise and other disciplines.
He most often published in these fields:
- Synthetic biology (25.34%)
- Control theory (15.07%)
- Computational biology (12.33%)
What were the highlights of his more recent work (between 2018-2021)?
- Synthetic biology (25.34%)
- Computational biology (12.33%)
- RNA (3.42%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Synthetic biology, Computational biology, RNA, Markov chain and DNA.
He merges Synthetic biology with Host in his study.
His Computational biology research is multidisciplinary, incorporating elements of Gene expression, Gene, Function, Software portability and Ribozyme.
His Markov chain study combines topics from a wide range of disciplines, such as Measure, Bounded function and Applied mathematics.
His research integrates issues of Combinatorial chemistry, Nucleic acid and Self-assembly in his study of DNA.
His work in Complex system addresses issues such as Nonlinear system, which are connected to fields such as Mathematical optimization.
Between 2018 and 2021, his most popular works were:
- Host-aware synthetic biology (31 citations)
- Whole-Cell Biosensor with Tunable Limit of Detection Enables Low-Cost Agglutination Assays for Medical Diagnostic Applications (19 citations)
- Bounding the stationary distributions of the chemical master equation via mathematical programming. (11 citations)
In his most recent research, the most cited papers focused on:
- Gene
- Artificial intelligence
- DNA
Computational biology, Applied mathematics, Markov chain, Truncation and Gene are his primary areas of study.
His work on Synthetic biology as part of general Computational biology study is frequently connected to Host, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His study in Applied mathematics is interdisciplinary in nature, drawing from both Irreducibility, State, State space, Linear equation and Error detection and correction.
He studied Markov chain and Measure that intersect with Distribution.
His work on Gene expression, Synthetic construct and microRNA as part of general Gene research is often related to Circuit performance, thus linking different fields of science.
His Function study integrates concerns from other disciplines, such as Resource, RNA-binding protein and Endogeny.
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