Machine Learning (ML) techniques are increasingly being used to address problems in bioinformatics and computational biology. ML based methods (e.g., support vector machines, neural networks, markov models, graphical models) have been successful in analysing life science data due to their capabilities in handling randomness and uncertainty of data noise and in generalization. Therefore, ML based techniques have been widely applied to discover and mine the knowledge in the databases and has indeed gained a lot of success in this research area. Several learning algorithms are available in the present literature. Therefore, researchers are facing difficulties in choosing the best technique that can be applied to their datasets. ML in Bioinformatics is an indispensable resource for biologists, computer scientists, mathematicians, engineers, researchers, physicians, clinicians, and medical informaticists.

The goal of this session is to bring together professionals, researchers, and practitioners in the area of bioinformatics to present, discuss, and share the latest findings in the field, and exchange ideas that address real-world problems with real-world solutions.