The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization. Here, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Comparative benchmarks performed on an updated independent dataset of proteins show that DeepSig is the current best performing method, scoring better than other available state-of-the-art approaches on both signal peptide detection and precise cleavage-site identification. DeepSig is available as both standalone program and web server at https://deepsig.biocomp.unibo.it
Signal peptides are short, cleavable, N-terminal peptides (from 15 up to 50 residue long) that are p...
Knowledge about protein-protein interactions is beneficial in understanding cellular mechanisms. Pro...
Identification of phosphorylation sites is an important step in the function study and drug design o...
The identification of signal peptides in protein sequences is an important step toward protein local...
MOTIVATION: The identification of signal peptides in protein sequences is an important step toward p...
Motivation: The identification of signal peptides in protein sequences is an important step toward ...
We present here a neural network-based method for detection of signal peptides (abbreviation used: S...
Neural networks are often used in protein sequence analysis. However, the results are unreliable, ma...
We have developed a new method for identification of signal peptides and their cleavage sites based ...
We have developed a new method for the identification of signal peptides and their cleavage sites ba...
Motivation: Automatic recognition of signal peptides and cleavage sites in proteins is a topical iss...
Protein inference, the identification of the protein set that is the origin of a given peptide profi...
Background: Amino-terminal signal peptides (SPs) are short regions that guide the targeting of secre...
signal peptide prediction accuracy by simulated neural network I.Ladunga1, F.Czakd2, I.Csabai2 and T...
Funding Information: This work was supported by the Academy of Finland [grant numbers 314445 and 328...
Signal peptides are short, cleavable, N-terminal peptides (from 15 up to 50 residue long) that are p...
Knowledge about protein-protein interactions is beneficial in understanding cellular mechanisms. Pro...
Identification of phosphorylation sites is an important step in the function study and drug design o...
The identification of signal peptides in protein sequences is an important step toward protein local...
MOTIVATION: The identification of signal peptides in protein sequences is an important step toward p...
Motivation: The identification of signal peptides in protein sequences is an important step toward ...
We present here a neural network-based method for detection of signal peptides (abbreviation used: S...
Neural networks are often used in protein sequence analysis. However, the results are unreliable, ma...
We have developed a new method for identification of signal peptides and their cleavage sites based ...
We have developed a new method for the identification of signal peptides and their cleavage sites ba...
Motivation: Automatic recognition of signal peptides and cleavage sites in proteins is a topical iss...
Protein inference, the identification of the protein set that is the origin of a given peptide profi...
Background: Amino-terminal signal peptides (SPs) are short regions that guide the targeting of secre...
signal peptide prediction accuracy by simulated neural network I.Ladunga1, F.Czakd2, I.Csabai2 and T...
Funding Information: This work was supported by the Academy of Finland [grant numbers 314445 and 328...
Signal peptides are short, cleavable, N-terminal peptides (from 15 up to 50 residue long) that are p...
Knowledge about protein-protein interactions is beneficial in understanding cellular mechanisms. Pro...
Identification of phosphorylation sites is an important step in the function study and drug design o...