Zachary B. Haiman

发表

MASSpy: Building, simulating, and visualizing dynamic biological models in Python using mass action kinetics

Bernhard O. Palsson, Daniel C. Zielinski, James T. Yurkovich, 2020, bioRxiv.

Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models

Daniel C. Zielinski, Abdelmoneim Amer Desouki, Zachary B. Haiman, 2018, Nature Communications.

Catalytic potential and disturbance rejection of glycolytic kinases in the human red blood cell

James T. Yurkovich, Zachary B. Haiman, B. Palsson, 2017, bioRxiv.

Mining all publicly available expression data to compute dynamic microbial transcriptional regulatory networks

Anand V. Sastry, Zachary B. Haiman, B. Palsson, 2021, bioRxiv.

Network-level allosteric effects are elucidated by detailing how ligand-binding events modulate utilization of catalytic potentials

Bernhard O Palsson, James T Yurkovich, James T. Yurkovich, 2018, PLoS Comput. Biol..

BioSimulators: a central registry of simulation engines and services for recommending specific tools

Jonathan R. Karr, Frank T. Bergmann, Ryan K. Spangler, 2022, Nucleic Acids Res..

Biological and Genetic Determinants of Glycolysis: Phosphofructokinase Isoforms Boost Energy Status of Stored Red Blood Cells and Transfusion Outcomes

Zachary B. Haiman, E. Hod, N. Roubinian, 2024, bioRxiv.

A data-driven approach for timescale decomposition of biochemical reaction networks

Zachary B. Haiman, Amir Akbari, Bernhard O. Palsson, 2024, mSystems.

Modeling Red Blood Cell Metabolism in the Omics Era

Zachary B. Haiman, A. Key, A. D’Alessandro, 2023, Metabolites.

A data-driven approach for timescale decomposition of biochemical reaction networks

Zachary B. Haiman, B. Palsson, Amir Akbari, 2023, bioRxiv.

Biological and genetic determinants of glycolysis: Phosphofructokinase isoforms boost energy status of stored red blood cells and transfusion outcomes.

Zachary B. Haiman, E. Hod, N. Roubinian, 2024, Cell metabolism.