PubstractHelper: A Web-based Text-Mining Tool for Marking Sentences in Abstracts from PubMed Using Multiple User-Defined Keywords

While a huge amount of information about biological literature can be obtained by searching the PubMed database, reading through all the titles and abstracts resulting from such a search for useful information is inefficient. Text mining makes it possible to increase this efficiency. Some websites use text mining to gather information from the PubMed database; however, they are database-oriented, using pre-defined search keywords while lacking a query interface for user-defined search inputs. We present the PubMed Abstract Reading Helper (PubstractHelper) website which combines text mining and reading assistance for an efficient PubMed search. PubstractHelper can accept a maximum of ten groups of keywords, within each group containing up to ten keywords. The principle behind the text-mining function of PubstractHelper is that keywords contained in the same sentence are likely to be related. PubstractHelper highlights sentences with co-occurring keywords in different colors. The user can download the PMID and the abstracts with color markings to be reviewed later. The PubstractHelper website can help users to identify relevant publications based on the presence of related keywords, which should be a handy tool for their research.

Availability

http://bio.yungyun.com.tw/ATM/PubstractHelper.aspx and http://holab.med.ncku.edu.tw/ATM/PubstractHelper.aspx     

Investigating microRNA-Target Interaction-Supported Tissues in Human Cancer Tissues Based on miRNA and Target Gene Expression Profiling

Recent studies have revealed that a small non-coding RNA, microRNA (miRNA) down-regulates its mRNA targets. This effect is regarded as an important role in various biological processes. Many studies have been devoted to predicting miRNA-target interactions. These studies indicate that the interactions may only be functional in some specific tissues, which depend on the characteristics of an miRNA. No systematic methods have been established in the literature to investigate the correlation between miRNA-target interactions and tissue specificity through microarray data. In this study, we propose a method to investigate miRNA-target interaction-supported tissues, which is based on experimentally validated miRNA-target interactions. The tissue specificity results by our method are in accordance with the experimental results in the literature.

Availability and Implementation

Our analysis results are available at http://tsmti.mbc.nctu.edu.tw/ and http://www.stat.nctu.edu.tw/hwang/tsmti.html.     

Uroporphyrinogen Decarboxylase as a Potential Target for Specific Components of Traditional Chinese Medicine: A Virtual Screening and Molecular Dynamics Study

Uroporphyrinogen decarboxylase (UROD) has been suggested as a protectant against radiation for head and neck cancer (HNC). In this study, we employed traditional Chinese medicine (TCM) compounds from TCM nawiaT@esabataD (http://tcm.cmu.edu.tw/) to screen for drug-like candidates with potential UROD inhibition characteristics using virtual screening techniques. Isopraeroside IV, scopolin, and nodakenin exhibited the highest Dock Scores, and were predicted to have good Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties. Two common moieties, 2H-chromen-2-one and glucoside, were observed among the top TCM candidates. Cross comparison of the docking poses indicated that candidates formed stable interactions with key binding and catalytic residues of UROD through these two moieties. The 2H-chromen-2-one moiety enabled pi-cation interactions with Arg37 and H-bonds with Tyr164. The glucoside moiety was involved in forming H-bonds with Arg37 and Asp86. From our computational results, we propose isopraeroside IV, scopolin, and nodakenin as ligands that might exhibit drug-like inhibitory effects on UROD. The glucoside and 2H-chromen-2-one moieties may potentially be used for designing inhibitors of UROD.     

A precise and scalable method for querying genes in chromosomal banding regions based on cytogenetic annotations

Motivation: Staining the human metaphase chromosomes revealscharacteristic banding patterns known as cytogenetic bands orcytobands. Using technologies based on metaphase chromosomes,researchers have accumulated much knowledge about the correlationsbetween human diseases and specific cytoband aberrations, indicatingthe presence of disease-associated genes in those bands. Withthe progress of human genome project and techniques such asfluorescent in situ hybridization, many genes have been assignedto the cytobands and annotated in public databases, making itpossible to find all genes in the disease-related cytobandsthrough database queries. However, finding genes in cytobandsremains an imprecise process, partly due to the insufficiencyof current methods for cytoband queries, especially for thosebased on cytogenetic annotations. Results: By transforming the cytoband annotations into numericalsegments, a new query method is developed that is able to accuratelydefine any cytogenetic ranges in human chromosomes. A querysystem (designated cytoband query sys CQS) is implemented usingcytogenetic annotations in the public domain. Judged by a performancetest, CQS executed as accurately as expected using cytogeneticannotations from NCBI Map Viewer. The new method is scalableand can be applied to genomes from other species. Availability: The CQS is freely accessible over the Internetat http://moris.csie.ncku.edu.tw/cqs/ Contact: clh9{at}mail.ncku.edu.tw Supplementary information: http://moris.csie.ncku.edu.tw/cqs/     

Molluscan fauna of Gueishan Island,Taiwan

This dataset records the occurrence and inventory of molluscan fauna on Gueishan Island, the only active volcanic island in Taiwan, based on the literature survey and field investigation conducted between 2011 and 2012. The literature review involved seven studies published from 1934 to 2003, which collectively reported 112 species from 61 genera and 37 families of Mollusca on Gueishan Island. Through our field investigation, we identified 34 species from 28 genera and 23 families. Fourteen of these species were new records on Gueishan Island: Liolophura japonica, Lottia luchuana, Nerita costata, Nerita rumphii, Diplommatina suganikeiensis, Littoraria undulata, Solenomphala taiwanensis, Assiminea sp., Siphonaria laciniosa, Laevapex nipponica, Carychium hachijoensis, Succinea erythrophana, Zaptyx crassilamellata, and Allopeas pyrgula. In Total, there are 126 species from 71 genera and 45 families of Mollusca on Gueishan Island. These data have been published through GBIF [http://taibif.org.tw/ipt/resource.do?r=gueishan_island] and integrated into the Taiwan Malacofauna Database (http://shell.sinica.edu.tw/).