Machine Learning in Bioinformatics

Machine Learning in Bioinformatics is a research topic within Molecular Biology. Science Explorer counts 26k research works in it since 1950. 9.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the prediction of protein subcellular localization using various computational methods such as amino acid composition, machine learning algorithms like support vector machines, and the analysis of signal peptides and transmembrane topology. The research aims to improve the accuracy and reliability of predicting the subcellular location of proteins, which has significant implications for understanding protein function and cellular processes.

• Subcellular Localization
• Protein
• Prediction
• Amino Acid Composition
• Machine Learning
• Support Vector Machines
• Signal Peptides
• Transmembrane Topology
• Enzyme Subfamily Classes
• Bioinformatics