Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Daniel C. Zielinski"'
Autor:
Yujiro Hirose, Daniel C. Zielinski, Saugat Poudel, Kevin Rychel, Jonathon L. Baker, Yoshihiro Toya, Masaya Yamaguchi, Almut Heinken, Ines Thiele, Shigetada Kawabata, Bernhard O. Palsson, Victor Nizet
Publikováno v:
mSystems, Vol 9, Iss 9 (2024)
ABSTRACT Streptococcus pyogenes is responsible for a range of diseases in humans contributing significantly to morbidity and mortality. Among more than 200 serotypes of S. pyogenes, serotype M1 strains hold the greatest clinical relevance due to thei
Externí odkaz:
https://doaj.org/article/370f8241006e4225bac7c0888054f2d2
Autor:
Christopher Dalldorf, Kevin Rychel, Richard Szubin, Ying Hefner, Arjun Patel, Daniel C. Zielinski, Bernhard O. Palsson
Publikováno v:
mSystems, Vol 9, Iss 7 (2024)
ABSTRACT Fast growth phenotypes are achieved through optimal transcriptomic allocation, in which cells must balance tradeoffs in resource allocation between diverse functions. One such balance between stress readiness and unbridled growth in E. coli
Externí odkaz:
https://doaj.org/article/4144198f5ea442bb88a2dd0454d94938
Autor:
Daniel C. Zielinski, Marta R.A. Matos, James E. de Bree, Kevin Glass, Nikolaus Sonnenschein, Bernhard O. Palsson
Publikováno v:
Metabolic Engineering Communications, Vol 18, Iss , Pp e00234- (2024)
Kinetic models of metabolism are promising platforms for studying complex metabolic systems and designing production strains. Given the availability of enzyme kinetic data from historical experiments and machine learning estimation tools, a straightf
Externí odkaz:
https://doaj.org/article/a3ef3cb9991f4cb2b3f475da646a4313
Autor:
Jonathan Josephs-Spaulding, Akanksha Rajput, Ying Hefner, Richard Szubin, Archana Balasubramanian, Gaoyuan Li, Daniel C. Zielinski, Leonie Jahn, Morten Sommer, Patrick Phaneuf, Bernhard O. Palsson
Publikováno v:
mSystems, Vol 9, Iss 3 (2024)
ABSTRACTLimosilactobacillus reuteri, a probiotic microbe instrumental to human health and sustainable food production, adapts to diverse environmental shifts via dynamic gene expression. We applied the independent component analysis (ICA) to 117 RNA-
Externí odkaz:
https://doaj.org/article/0c560a62b2a84aecbbd7f328d4ed4532
Autor:
Sourav Chowdhury, Daniel C. Zielinski, Christopher Dalldorf, Joao V. Rodrigues, Bernhard O. Palsson, Eugene I. Shakhnovich
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-14 (2023)
Abstract Elucidating intracellular drug targets is a difficult problem. While machine learning analysis of omics data has been a promising approach, going from large-scale trends to specific targets remains a challenge. Here, we develop a hierarchic
Externí odkaz:
https://doaj.org/article/487eb402d5bc4afe9dded197f9fac91e
Autor:
Yujiro Hirose, Saugat Poudel, Anand V. Sastry, Kevin Rychel, Cameron R. Lamoureux, Richard Szubin, Daniel C. Zielinski, Hyun Gyu Lim, Nitasha D. Menon, Helena Bergsten, Satoshi Uchiyama, Tomoki Hanada, Shigetada Kawabata, Bernhard O. Palsson, Victor Nizet
Publikováno v:
mSystems, Vol 8, Iss 3 (2023)
ABSTRACT Streptococcus pyogenes can cause a wide variety of acute infections throughout the body of its human host. An underlying transcriptional regulatory network (TRN) is responsible for altering the physiological state of the bacterium to adapt t
Externí odkaz:
https://doaj.org/article/3b43ea8193f84eecb3e9e294107d3b83
Publikováno v:
Metabolites, Vol 13, Iss 11, p 1127 (2023)
Pathway analysis is ubiquitous in biological data analysis due to the ability to integrate small simultaneous changes in functionally related components. While pathways are often defined based on either manual curation or network topological properti
Externí odkaz:
https://doaj.org/article/7e25c32798c148ecbaabcdeb786656a0
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-19 (2021)
Evolution selects for the fittest but must operate within the realm of the physically possible. Here, the authors present a theoretical framework that allows them to explore how ten abiotic constraints can shape the operation, regulation, and adaptat
Externí odkaz:
https://doaj.org/article/47788bcb4646471292db38ad57312462
Autor:
David Heckmann, Colton J. Lloyd, Nathan Mih, Yuanchi Ha, Daniel C. Zielinski, Zachary B. Haiman, Abdelmoneim Amer Desouki, Martin J. Lercher, Bernhard O. Palsson
Publikováno v:
Nature Communications, Vol 9, Iss 1, Pp 1-10 (2018)
Experimental data on enzyme turnover numbers is sparse and noisy. Here, the authors use machine learning to successfully predict enzyme turnover numbers for E. coli, and show that using these to parameterize mechanistic genome-scale models enhances t
Externí odkaz:
https://doaj.org/article/4253a943492247b28ad5cd46f32d93b3
Publikováno v:
Nature Communications, Vol 9, Iss 1, Pp 1-9 (2018)
The catalytic efficiency of many enzymes is lower than the theoretical maximum. Here, the authors combine genome-scale metabolic modeling with population genetics models to simulate enzyme evolution, and find that strong epistasis limits turnover num
Externí odkaz:
https://doaj.org/article/4f3a3407855745988954321965d01387