ABSTRACT
Successful intelligence theory suggests that creativity is necessary for personal achievement outside of intelligence. Unlike intelligence, creativity can develop in a supportive environment. People should consider the situation of disadvantaged groups, which are characterized by low personal achievement and a bad growth environment in creativity evaluation from a caring perspective. This study focuses on the effect of the creator's situation on creative evaluation and the role of the rater's empathy (i.e., cognitive empathy and affective empathy) and sympathy in creative evaluation. Four pairs of creator's situations (by age, physical state, family situation, and economic state) were designed to represent people with disadvantages or advantages. A between-subject design was used with 590 undergraduate students randomly assigned to eight sub-conditions. The participants were asked to assess three products in eight situations. The rater's empathy and sympathy in creativity evaluation were explored in the overall disadvantage (N = 300) and advantage (N = 290) conditions. The results showed that the participants only provided significantly higher ratings to the creative product made by a child. Cognitive empathy only predicted a creative rating under disadvantaged conditions, and affective empathy negatively moderated this effect. Affective empathy only predicted a creative rating under advantage conditions, and cognitive empathy positively moderated this effect. Affective empathy only predicted a creative rating under advantage conditions, and cognitive empathy positively moderated this effect. The possible mechanisms of the effect and implications for the establishment of a supportive environment for creativity and creativity teaching practice were discussed.
ABSTRACT
Several high-throughput technologies have been developed to probe RNA base pairs and loops at the transcriptome level in multiple species. However, to obtain the final RNA secondary structure, extensive effort and considerable expertise is required to statistically process the probing data and combine them with free energy models. Therefore, we developed an RNA secondary structure prediction server that is enhanced by experimental data (RNAex). RNAex is a web interface that enables non-specialists to easily access cutting-edge structure-probing data and predict RNA secondary structures enhanced by in vivo and in vitro data. RNAex annotates the RNA editing, RNA modification and SNP sites on the predicted structures. It provides four structure-folding methods, restrained MaxExpect, SeqFold, RNAstructure (Fold) and RNAfold that can be selected by the user. The performance of these four folding methods has been verified by previous publications on known structures. We re-mapped the raw sequencing data of the probing experiments to the whole genome for each species. RNAex thus enables users to predict secondary structures for both known and novel RNA transcripts in human, mouse, yeast and Arabidopsis The RNAex web server is available at http://RNAex.ncrnalab.org/.
Subject(s)
Nucleic Acid Conformation , Polymorphism, Single Nucleotide , RNA/chemistry , Transcriptome , User-Computer Interface , Animals , Arabidopsis/genetics , Arabidopsis/metabolism , Base Pairing , Computer Graphics , High-Throughput Screening Assays , Humans , Internet , Mice , Molecular Sequence Annotation , RNA/genetics , RNA Editing , RNA Folding , Saccharomyces cerevisiae/genetics , Saccharomyces cerevisiae/metabolism , ThermodynamicsABSTRACT
The identification of cancer genes remains a main aim of cancer research. With the advances of high-throughput sequencing technologies, thousands of novel cancer genes were identified through recurrent mutation analyses and differential expression analyses between normal tissues and tumors in large populations. Many databases were developed to document the cancer genes. However, no public database providing both cancer protein-coding genes and cancer lncRNAs is available presently. Here, we present the Catalogue of Cancer Genes (CCG) database (http://ccg.xingene.net), a catalogue of cancer genes. It includes both well-supported and candidate cancer protein-coding genes and cancer lncRNAs collected from literature search and public databases. In addition, uniform genomic aberration information (such as somatic mutation and copy number variation) and drug-gene interactions were assigned to cancer genes in the database. CCG represents an effort on integrative assembly of well-supported and candidate cancer protein-coding and long noncoding RNA genes and takes advantages of high-throughput sequencing results on large populations. With the help of CCG, users can easily access a comprehensive list of cancer genes as well as genomic aberration related with these genes. The availability of integrative information will facilitate the understanding of cancer mechanisms. In addition, drug-gene information in CCG provides a useful guide to the development of new anti-cancer drugs and selection of rational combination therapies.
