For many biomedical modelling tasks a number of different types of data may influence predictions made by the model. An established approach to pursuing supervised learning with ...
Yiming Ying, Colin Campbell, Theodoros Damoulas, M...
Analysis of biological data often involves large data sets and computationally expensive algorithms. Databases of biological data continue to grow, leading to an increasing demand ...
—We present a new algorithm, ChemAlign, that uses physicochemical properties and secondary structure elements to create biologically relevant multiple sequence alignments (MSAs)....
Hyrum Carroll, Mark J. Clement, Quinn Snell, David...
One of the major problems in biological data integration is that many data sources are stored as flat-files, with a variety of different layouts. Integrating data from such sour...
Kaushik Sinha, Xuan Zhang, Ruoming Jin, Gagan Agra...
—We consider the problem of identifying motifs, recurring or conserved patterns, in the sets of biological sequences. To solve this task, we present new deterministic and exact a...