Advance of Peptide Detectability Prediction on Mass Spectrometry Platform in Proteomics / 分析化学

As the complexity of samples and experimental processes, the repeatability of mass spectrometry experiments is still not satisfactory, the results of peptide identification and quantification show high randomicity), the probability of peptide being detected by mass spectrometry in proteome research, especially in quantitative proteomic study, has received much attention. Therefore, a lot of experimental researches have been done, as well as a number of computational prediction methods have been developed. In this article, we summarized the important factors impacting the peptide detectability, investigated the existing prediction methods) and reviewed their applications in experimental study.

Design of 16 S rRNA-based Oligonucleotide Array Using Group-specific Non-unique Probes in Large Scale Bacteria Detection / 生物化学与生物物理进展

With thousands of sequenced 16 S rRNA genes available,and advancements in oligonucleotide microarray technology,the detection of microorganisms in microbial communities consisting of hundreds of species may be possible.The existing algorithms developed for sequence-specific probe design are not suitable for applications in large-scale bacteria detection due to the lack of coverage,flexibility and efficiency.Many other strategies developed for group-specific probe design focus on how to find a unique group-specific probe that can specifically detect all target sequences of a group.Unique group-specific probe for each group can not always be found.Hence,it is necessary to design non-unique probes.Each probe can specifically detect target sequences of a different subgroup.Combination of multiple probes can achieve higher coverage.However,it is a time-consuming task to evaluate all possible combinations.A feasible algorithm using relative entropy and genetic algorithm (GA) to design group-specific non-unique probes was presented.