The emphasis is mainly on discrete algorithms and machine-learning methods that address important problems in molecular biology, that are founded on sound models, that are computationally efficient, and that provide evidence of their potential usefulness in practice, preferably by testing on appropriately chosen simulated or real datasets. The goal is to present recent research results, including significant work-in-progress, and to identify and explore directions of future research. This year it is colocated with ACM-BCB 2021.