This has resulted in subcellular localization prediction becoming one of the challenges being successfully aided by bioinformatics, and machine learning.
[5] Subsequent tools and websites have been released using techniques such as artificial neural networks, support vector machine and protein motifs.
[10] SCLpred-EMS is another tool powered by Artificial neural networks that classify proteins into endomembrane system and secretory pathway (EMS) versus all others.
Knowledge of the subcellular localization of a protein can significantly improve target identification during the drug discovery process.
Bacterial cell surface and secreted proteins are also of interest for their potential as vaccine candidates or as diagnostic targets.
By using prediction a high number of proteins can be assessed in order to find candidates that are trafficked to the desired location.