@inbook{723b9cb1a26a42a89440d973db1d4d0f,
title = "Overview of Bioinformatics Software and Databases for Metabolic Engineering",
abstract = "The explosion of the {"}omics{"} era has introduced a growing number of sets and tools that facilitate molecular interrogation of the metabolome. These include various bioinformatics and pharmacogenomics resources that can be utilized independently or collectively to facilitate metabolic engineering across disease, clinical oncology, and understanding of molecular changes across larger systems. This review provides starting points for accessing publicly available data and computational tools that support assessment of metabolic profiles and metabolic regulation, providing both a depth-and-breadth approach toward understanding the metabolome. We focus in particular on pathway databases and tools, which provide in-depth analysis of metabolic pathways, which is at the heart of metabolic engineering.",
keywords = "Computational Biology, Databases, Factual, Metabolic Engineering, Metabolome, Metabolomics, Software",
author = "Gendoo, {Deena M A}",
note = "{\textcopyright} 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.",
year = "2022",
month = oct,
day = "14",
doi = "10.1007/978-1-0716-2617-7_13",
language = "English",
isbn = "978-1-0716-2616-0",
series = "Methods in molecular biology (Clifton, N.J.)",
publisher = "Springer",
pages = "265--274",
editor = "{ Selvarajoo}, Kumar",
booktitle = "Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology",
}