File upload size is currently capped at 500MB. For assistance adding larger files, please contact discovery-access-systems@nottingham.ac.uk
Thumbnail Image

A linear, binary classifier to predict bacterial biofilm formation on polyacrylates

Publication Date
December 21, 2022
Creators
Description
Research data and Python code to undertake machine learning to predict bacterial attachment to polyacrylates.
External URI
DOI
Subjects (LCSH)

Biofilms

Attachment mechanisms...

Polymers

Subjects

ToF-SIMS; Python code...

Subjects (JACS)

Biological Sciences::...

Subjects (LC)

Q Science::QR Microbi...

Divisions
University of Nottingham, UK Campus::Faculty of Science::School of Pharmacy
Data type
Python source code, Microsoft Excel datafile
Funders
Grant Number
EP/N006615/1
Data collection method
ToF-SIMs
Resource languages
English
Publisher
The University of Nottingham
Date Issued
December 21, 2022
Except where otherwise noted, this item's license is described as
File(s)
Thumbnail Image
Name

readme.txt

Description
Readme explaining contents of Archive.zip (Molecular structures; Descriptor generation; Datasets and modelling)
Size

287 B

Format

Text

Checksum (MD5)

0b074e1ac1dc5d94efa96280d7e80923

Thumbnail Image
Name

c496 Pathogen_attachment data.xlsx

Description
Pathogen attachment data (processed)
Size

213.12 KB

Format

Microsoft Excel XML

Checksum (MD5)

494449295e134362cbc7b08ba1dd2afd