A challenging problem in Bioinformatics is to predict protein structure, properties, activities or interactions from their aminoacid sequences. Sequence-derived physicochemical features of proteins have been used to support the development of Machine Learning (ML) models. However, tools and platforms to calculate features from protein sequences and train ML models are scarce and have limitations in terms of performance, user-friendliness and domains of application.This study was supported by FCT through project PTDC/CCI-BIO/28200/2017 and the strategic funding of UID/BIO/04469/2020, and also by the European Regional Development Fund under the scope of Norte2020, through the projects DeepBio (ref. NORTE-01-0247-FEDER-039831). This work was a...
Background: The huge difference between the number of known sequences and known tertiary structures ...
The protein sequence determines how it will fold into its unique three-dimensional structure. Once f...
Background: Machine Learning (ML) has a number of demonstrated applications in protein prediction ta...
The field of protein data mining has been growing rapidly in the last years. To characterize protein...
One of the most challenging problems in bioinformatics is to computationally characterize sequences,...
The huge difference between the number of known sequences and known tertiary structures has justifie...
A number of protein sequences are found and added to the database but its functional properties are ...
Computational tools for the analysis of protein data and the prediction of biological properties are...
Summary: Sequence-derived structural and physiochemical features have been frequently used for analy...
Proteins play a crucial roll in all biological processes. The wide range of protein functions is mad...
Abstract: In nature, protein chain interactions (Pro-ChInt) of single- / multi-protein, a common but...
The development of high-throughput measurement techniques resulted in rapidlyincreasing amounts of b...
Summary: Sequence-derived structural and physiochemical features have been frequently used for analy...
Recent progress in fundamental biological sciences and medicine has considerably increased the quant...
none2During the last decade there has been a tremendous growth in the amount of protein data. Machin...
Background: The huge difference between the number of known sequences and known tertiary structures ...
The protein sequence determines how it will fold into its unique three-dimensional structure. Once f...
Background: Machine Learning (ML) has a number of demonstrated applications in protein prediction ta...
The field of protein data mining has been growing rapidly in the last years. To characterize protein...
One of the most challenging problems in bioinformatics is to computationally characterize sequences,...
The huge difference between the number of known sequences and known tertiary structures has justifie...
A number of protein sequences are found and added to the database but its functional properties are ...
Computational tools for the analysis of protein data and the prediction of biological properties are...
Summary: Sequence-derived structural and physiochemical features have been frequently used for analy...
Proteins play a crucial roll in all biological processes. The wide range of protein functions is mad...
Abstract: In nature, protein chain interactions (Pro-ChInt) of single- / multi-protein, a common but...
The development of high-throughput measurement techniques resulted in rapidlyincreasing amounts of b...
Summary: Sequence-derived structural and physiochemical features have been frequently used for analy...
Recent progress in fundamental biological sciences and medicine has considerably increased the quant...
none2During the last decade there has been a tremendous growth in the amount of protein data. Machin...
Background: The huge difference between the number of known sequences and known tertiary structures ...
The protein sequence determines how it will fold into its unique three-dimensional structure. Once f...
Background: Machine Learning (ML) has a number of demonstrated applications in protein prediction ta...