The EnzymeML data repository of the Institute of Biochemistry and Technical Biochemistry.
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111 to 120 of 165 Results
pH 7.0+7.5 30deg standards.txt
Feb 2, 2023 - From raw data to kinetic parameters: an EnzymeML-based workflow for reproducible enzyme kinetics
Plain Text - 5.2 KB - MD5: 184b87e740e03cc31253ba78dbd670c6
pH 7.0+7.5 35deg scan.txt
Feb 2, 2023 - From raw data to kinetic parameters: an EnzymeML-based workflow for reproducible enzyme kinetics
Plain Text - 20.5 KB - MD5: 4668d7b496fd6489dc7e3fa0a2496fe8
pH 7.0+7.5 35deg standards.txt
Feb 2, 2023 - From raw data to kinetic parameters: an EnzymeML-based workflow for reproducible enzyme kinetics
Plain Text - 5.2 KB - MD5: 31f4f3620ab77bd86f5a3410ba613610
pH 7.0+7.5 40deg scan.txt
Feb 2, 2023 - From raw data to kinetic parameters: an EnzymeML-based workflow for reproducible enzyme kinetics
Plain Text - 20.5 KB - MD5: f295011922d54b0dc40e68605797945c
pH 7.0+7.5 40deg standards.txt
Feb 2, 2023 - From raw data to kinetic parameters: an EnzymeML-based workflow for reproducible enzyme kinetics
Plain Text - 5.2 KB - MD5: 722401bdc02a5915f6f2abf0c38e2c6a
pH 7.0+7.5 45deg scan.txt
Feb 2, 2023 - From raw data to kinetic parameters: an EnzymeML-based workflow for reproducible enzyme kinetics
Plain Text - 20.5 KB - MD5: 84686820f14a6d5341c6f3730ae86458
pH 7.0+7.5 45deg standards.txt
Feb 2, 2023 - From raw data to kinetic parameters: an EnzymeML-based workflow for reproducible enzyme kinetics
Plain Text - 5.2 KB - MD5: 0cd6cde58a26060e03ebf37586a0b8a2
plotter.py
Feb 2, 2023 - From raw data to kinetic parameters: an EnzymeML-based workflow for reproducible enzyme kinetics
Python Source Code - 1.5 KB - MD5: fc7c9351f82f8521fa7d6713feba1fef
pNA-standard.xlsx
Feb 2, 2023 - From raw data to kinetic parameters: an EnzymeML-based workflow for reproducible enzyme kinetics
MS Excel Spreadsheet - 22.5 KB - MD5: 23c61c775ec7caf24e1ee2766ad41f81
p-NP_standard.xlsx
Feb 2, 2023 - From raw data to kinetic parameters: an EnzymeML-based workflow for reproducible enzyme kinetics
MS Excel Spreadsheet - 18.5 KB - MD5: 61f059e10252a2624664de7fef850bfc
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