第1155回千葉医学会例会・臓器制御外科学教室談話会

DE based analysis results for static and temporal comparisons. DE based analyses for static (P21WT vs. P21KO) (S5.1) and temporal (P0 vs. P21WT and P0 vs. P21KO) comparisons (S5.2, S5.3). (XLSX 4196 kb

Grammatical formalisms for RNA structure analysis

Since the function of a molecular sequence depends on its structure, analyzing RNA structures is essential to create new drugs and understand genetic diseases. Pseudoknots are one type of RNA structures that have attracted a lot of interest in recent years, especially as it became possible to address the computational complexity associated with modeling this type of structures. Pseudoknot structures have functional importance since they appear, for example, in viral genome RNAs and ribozyme active sites. In predicting RNA structures, computational methods are less expensive than other methods such as nuclear magnetic resonance and x-ray crystallography. A relatively new approach to structure analysis, namely, the grammatical approach has attracted the attention of many researchers, because it can model long range interactions. Grammars offer a natural and concise way to model DNA, RNA, and protein sequences. In this research, we aim to facilitate for biologists the use of grammatical models for RNA structure analysis through the automation of the grammar building step. We focus on grammatical models capable of representing pseudoknots. ^ The main contribution of this research is the development of an RNA structure analysis framework, TAGRNAInf. The framework is capable of analyzing RNA structures including pseudoknots. It currently addresses two RNA structure analysis problems: structure identification and RNA folding, and it can be expanded to address other problems like structural classification and motif search. The approach adapted in this solution is a grammatical inference approach that has a learning algorithm for a grammatical model capable of representing RNA pseudoknots (Tree Adjoining Grammars for RNA, TAG RNA) at the core of its learning phase. There has been previous research on the use of grammatical approach for RNA structure analysis including pseudoknots in which a specific model is built for a certain family of RNAs. However, there has been limited research on the use of grammatical inference for RNA structure analysis. TAGRNAInf. is the first complete framework for RNA structure analysis including pseudoknot, based on grammatical inference, that has been experimentally tested and yielded results competitive to other available methods. ^ As a part of this research, we also developed a new grammatical model, Linked Single Adjoining-Tree Adjoining Grammars (LSA–TAG), capable of representing pseudoknots. We have developed a grammatical inference algorithm for LSA–TAG that can learn the grammar for a family of RNA structures from example sequences. This inference algorithm has proven to be mainly of theoretical interest.

Do Online Firms Individualize Search Results? An Empirical Analysis of Individualization on Amazon

Online markets offer sellers access to buyers’ information and, thus, the potential to alter prices and products accordingly. In light of this, we undertook an empirical analysis to test for individualization on Amazon.com. We collect data from individuals recruited to shop for household items. Our results indicate evidence of individualization of search results and net prices (via coupons). We found, contrary to what was expected, that demographic, geolocation, and account information play an insignificant role in individualization of search results. Thus, we conclude that individualization is based on more dynamic information, e.g., online browsing behavior. This highlights the fact that sellers’ need for (and use of) buyer information goes beyond the simple information accessible from the buyers’ accounts to a more rigorous monitoring of buyers’ online behavior

Additional file 6: Table S5. of Network-based bioinformatics analysis of spatio-temporal RNA-Seq data reveals transcriptional programs underpinning normal and aberrant retinal development

DE based analysis results for static and temporal comparisons. DE based analyses for static (P21WT vs. P21KO) (S5.1) and temporal (P0 vs. P21WT and P0 vs. P21KO) comparisons (S5.2, S5.3). (XLSX 4196 kb

Dosage Compensation and Gene Expression of the X Chromosome in Sheep

Ohno’s hypothesis predicts that the expression of the single X chromosome in males needs compensatory upregulation to balance its dosage with that of the diploid autosomes. Additionally, X chromosome inactivation ensures that quadruple expression of the two X chromosomes is avoided in females. These mechanisms have been actively studied in mice and humans but lag behind in domestic species. Using RNA sequencing data, we analyzed the X chromosome upregulation in sheep fetal tissues from day 135 of gestation under control, over or restricted maternal diets (100%, 140% and 60% of National Research Council Total Digestible Nutrients), and in conceptuses, juvenile, and adult somatic tissues. By computing the mean expression ratio of all X-linked genes to all autosomal genes (X:A), we found that all samples displayed some levels of X chromosome upregulation. The degrees of X upregulation were not significant (P-value = 0.74) between ovine females and males in the same somatic tissues. Brain, however, displayed complete X upregulation. Interestingly, the male and female reproduction-related tissues exhibited divergent X dosage upregulation. Moreover, expression upregulation of the X chromosome in fetal tissues was not affected by maternal diets. Maternal nutrition, however, did change expression levels of several X-linked genes, such as sex determination genes SOX3 and NR0B1. In summary, our results showed that X chromosome upregulation occurred in nearly all sheep somatic tissues analyzed, thus support Ohno’s hypothesis in a new species. However, the levels of upregulation differed by different subgroups of genes such as those that are house-keeping and “dosage-sensitive”