Flowchart of the entire pipeline.

Flowchart of the entire pipeline.

<p>First, the raw data is filtered and cleaned, and converted to a binary data format for faster reading (see Section Data retrieval and preprocessing). Next, the general protein dataset is converted to a specific transporter dataset according to specified parameters (see Section Dataset creat...

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Bibliographic Details
Main Author: Andreas Denger (12111159) (author)
Other Authors: Volkhard Helms (35164) (author)
Published: 2024
Subjects:
Biochemistry
Medicine
Cell Biology
Genetics
Biotechnology
Infectious Diseases
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
various research fields
unlike previous approaches
supervised learning methods
sufficient sample size
strong class separability
provides important information
median f1 score
low sample count
key biological pathways
form complex networks
employ machine learning
training predictive models
dataset containing 98
95 ± 0
92 ± 0
87 ± 0
30 go terms
11 go terms
meta -) proteome
div >< p
creating training datasets
membrane transporters within
pipeline automatically reduced
training dataset
go terms
go datasets
membrane transporters
protein datasets
wide variety
wide range
transport proteins
transmembrane transporters
thaliana </
substrate transport
specific substrates
specific functions
respective functions
reducing redundancy
pipeline found
molecular functions
minimal redundancy
including plants
including biotechnology
hierarchical relationships
full redundancy
frequently annotated
covered proteins
coli </
cerevisiae </
cell eukaryotes
biology behind
automated pipeline
67 %,
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