Rotational hyperspectral scanner and related image reconstruction algorithm.

We design and implement a compact and lightweight hyperspectral scanner. Based on this, a novel rotational hyperspectral scanner was demonstrated. Different from translational scanning, rotational scanning is a moveless and stable scanning method.

A genetic algorithm-based weighted ensemble method for predicting transposon-derived piRNAs.

Background: Predicting piwi-interacting RNA (piRNA) is an important topic in the small non-coding RNAs, which provides clues for understanding the generation mechanism of gamete. To the best of our knowledge, several machine learning approaches have been proposed for the piRNA prediction, but there is still room for improvements.

Results: In this paper, we develop a genetic algorithm-based weighted ensemble method for predicting transposon-derived piRNAs.

Accurate Prediction of Transposon-Derived piRNAs by Integrating Various Sequential and Physicochemical Features.

Background: Piwi-interacting RNA (piRNA) is the largest class of small non-coding RNA molecules. The transposon-derived piRNA prediction can enrich the research contents of small ncRNAs as well as help to further understand generation mechanism of gamete.

Methods: In this paper, we attempt to differentiate transposon-derived piRNAs from non-piRNAs based on their sequential and physicochemical features by using machine learning methods.

Predicting drug side effects by multi-label learning and ensemble learning.

Background: Predicting drug side effects is an important topic in the drug discovery. Although several machine learning methods have been proposed to predict side effects, there is still space for improvements. Firstly, the side effect prediction is a multi-label learning task, and we can adopt the multi-label learning techniques for it.

Accurate prediction of immunogenic T-cell epitopes from epitope sequences using the genetic algorithm-based ensemble learning.

Background: T-cell epitopes play the important role in T-cell immune response, and they are critical components in the epitope-based vaccine design. Immunogenicity is the ability to trigger an immune response. The accurate prediction of immunogenic T-cell epitopes is significant for designing useful vaccines and understanding the immune system.