In this paper we describe a microcomputer program (HTP) for predicting the location and orientation of α-helical transmembrane segments in integral membrane proteins. HTP is a neural network- based tool which gives as output the protein membrane topology based on the statistical propensity of residues to be located in external and internal loops. This method, which uses single protein sequences as input to the network system, correctly predicts the topology of 71 out of 92 membrane proteins of putative membrane orientation, independently of the protein source
α-helical membrane proteins constitute 20-30% of all proteins in a cell and are involved in many ess...
Membrane proteins constitute a large and important class of proteins. They are responsible for many ...
International audienceOrienTM is a computer software that utilizes an initial definition of transmem...
In this paper we describe a microcomputer program (HTP) for predicting the location and orientation ...
We describe a neural network system that predicts the locations of transmembrane helices in integral...
Previously, we introduced a neural network system predicting locations of transmembrane helices (HTM...
Membrane proteins are key elements of the cell since they are associated with a variety of very impo...
Back-propagation, feed-forward neural networks are used to predict alpha-helical transmembrane segme...
Membrane proteins fulfil a number of tasks in cells, including signalling, cell-cell interaction, an...
Membrane proteins comprise around 20-30% of a typical proteome and play crucial roles in a wide vari...
An artificial neural network (NN) was trained to predict the topology of bacterial outer membrane (O...
Membrane proteins are of broad interest since they constitute a large fraction of the proteome in al...
We have developed a new approach for locating transmembrane domains in protein sequences based on hy...
The prediction of transmembrane helical segments (TMHs) in membrane proteins is an important field i...
Transmembrane helix (TMH) topology prediction is becoming a focal problem in bioinformatics because ...
α-helical membrane proteins constitute 20-30% of all proteins in a cell and are involved in many ess...
Membrane proteins constitute a large and important class of proteins. They are responsible for many ...
International audienceOrienTM is a computer software that utilizes an initial definition of transmem...
In this paper we describe a microcomputer program (HTP) for predicting the location and orientation ...
We describe a neural network system that predicts the locations of transmembrane helices in integral...
Previously, we introduced a neural network system predicting locations of transmembrane helices (HTM...
Membrane proteins are key elements of the cell since they are associated with a variety of very impo...
Back-propagation, feed-forward neural networks are used to predict alpha-helical transmembrane segme...
Membrane proteins fulfil a number of tasks in cells, including signalling, cell-cell interaction, an...
Membrane proteins comprise around 20-30% of a typical proteome and play crucial roles in a wide vari...
An artificial neural network (NN) was trained to predict the topology of bacterial outer membrane (O...
Membrane proteins are of broad interest since they constitute a large fraction of the proteome in al...
We have developed a new approach for locating transmembrane domains in protein sequences based on hy...
The prediction of transmembrane helical segments (TMHs) in membrane proteins is an important field i...
Transmembrane helix (TMH) topology prediction is becoming a focal problem in bioinformatics because ...
α-helical membrane proteins constitute 20-30% of all proteins in a cell and are involved in many ess...
Membrane proteins constitute a large and important class of proteins. They are responsible for many ...
International audienceOrienTM is a computer software that utilizes an initial definition of transmem...