Major Article Contributions by Some of our Chinese Authors in Bentham Science Publishers Journal; Current Bioinformatics


ImageArticle Title:

Integrative Approaches for microRNA Target Prediction: Combining Sequence Information and the Paired mRNA and miRNA Expression Profiles

Author(s): Naifang Su, Minping Qian and Minghua Deng


Gene regulation is a key factor in gaining a full understanding of molecular biology. microRNA (miRNA), a novel class of non-coding RNA, has recently been found to be one crucial class of post-transactional regulators, and play important roles in cancer. One essential step to understand the regulatory effect of miRNAs is the reliable prediction of their target mRNAs. Typically, the predictions are solely based on the sequence information, which unavoidably have high false detection rates. Recently, some novel approaches are developed to predict miRNA targets by integrating the typical algorithm with the paired expression profiles of miRNA and mRNA. Here we review and discuss these integrative approaches and propose a new algorithm called HCTarget. Applying HCtarget to the expression data in multiple myeloma, we predict target genes for ten specific miRNAs. The experimental verification and a loss of function study validate our predictions. Therefore, the integrative approach is a reliable and effective way to predict miRNA targets, and could improve our comprehensive understanding of gene regulation.

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Article Title: SubChlo-GO: Predicting Protein Subchloroplast Locations with Weighted Gene Ontology Scores

Author(s): Pufeng Du, Tingting Li, Xin Wang and Chao Xu


Chloroplasts are subcellular organelles found only in green plants and eukaryotic algae. Chloroplasts are of central importance in the photosynthesis process. The subchloroplast localizations of chloroplast proteins are critical in understanding their functions and important for fully decipher the photosynthesis process. Although there are several existing methods that computationally determine protein subchloroplast localizations, prediction performance and software availability can still be improved. We proposed a novel computational method, namely, the Weighted Gene Ontology Scores, to predict protein subchloroplast locations. This method can achieve at least 88% prediction accuracy on the benchmarking dataset, which is significantly higher than existing methods. SubChlo-GO, which is an easy-to-use webbased online service, has been constructed based on the proposed method. We hope that SubChlo-GO could be helpful in chloroplast proteome research.
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Article Title: Analysis of Gene Logic Networks for Arabidopsis
Author(s): Yansen Su, Shudong Wang, Eryan Li, Tao Song, Hui Yu and Dazhi Meng


External stimuli may activate the stress response in Arabidopsis thaliana. The molecules which play important roles in the stress response have been widely studied. However, the interactions, especially logic interactions, among these molecules, need to be studied. In this paper, logic networks are constructed based on gene expression profiles of Arabidopsis under the normal condition and four different stimuli conditions, respectively. It is found that the distribution of different types of 2-order logics in the gene logic network under the normal condition is different from the others. Furthermore, the logic networks of genes which play important roles are constructed and their dynamics are simulated. It is then observed that the number of attractors in the logic network for Arabidopsis under the normal condition is less than those under four external stimuli. It is also observed that the number of attractors with large attraction domain in the logic network for Arabidopsis under the normal condition is greater than those under four external stimuli. The results show that the distribution of different types of 2-order logics and the number of attractors clearly distinguish logic network under the normal condition from those under external stimuli conditions. Our studies will provide the theoretical basis for experimental studies on the stress response of Arabidopsis.

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Article Title: Periodic Correlation Structures in Bacterial and Archaeal Complete Genomes
Author(s): Zuo-Bing Wu


The periodic transference of nucleotide strings in bacterial and archaeal complete genomes is investigated by using the metric representation and the recurrence plot method. The generated periodic correlation structures exhibit four kinds of fundamental transferring characteristics: a single increasing period, several increasing periods, an increasing quasi-period and almost noincreasing period. The mechanism of the periodic transference is further analyzed by determining all long periodic nucleotide strings in the bacterial and archaeal complete genomes and is explained as follows: both the repetition of basic periodic nucleotide strings and the transference of non-periodic nucleotide strings would form the periodic correlation structures with approximately the same increasing periods.

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Author: Bentham Science Publishers

A major STM journal publisher of more than 100 online and print journals and related print/online book series, Bentham Science answers the information needs of scientists in the fields of pharmaceutical, biomedical, medical, engineering, technology, computer and social sciences.

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