scholarly journals Web Resource Categorization by Detecting Potential Relations

2008 ◽  
Vol 4 ◽  
pp. 103-113
Author(s):  
Minghua Pei ◽  
Kotaro Nakayama ◽  
Takahiro Hara ◽  
Shojiro Nishio
Keyword(s):  
Web Resource ◽  
Resource Categorization

scholarly journals Lantern: an integrative repository of functional annotations for lncRNAs in the human genome

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Swapna Vidhur Daulatabad ◽  
Rajneesh Srivastava ◽  
Sarath Chandra Janga
Keyword(s):  
Human Genome ◽  
Cellular Localization ◽  
Expression Profiles ◽  
Free Text ◽  
Dynamic Visualization ◽  
Specific Expression ◽  
Web Resource ◽  
Functional Dynamics ◽  
Non Coding Rnas ◽  
Retrieval Engine

Abstract Background With advancements in omics technologies, the range of biological processes where long non-coding RNAs (lncRNAs) are involved, is expanding extensively, thereby generating the need to develop lncRNA annotation resources. Although, there are a plethora of resources for annotating genes, despite the extensive corpus of lncRNA literature, the available resources with lncRNA ontology annotations are rare. Results We present a lncRNA annotation extractor and repository (Lantern), developed using PubMed’s abstract retrieval engine and NCBO’s recommender annotation system. Lantern’s annotations were benchmarked against lncRNAdb’s manually curated free text. Benchmarking analysis suggested that Lantern has a recall of 0.62 against lncRNAdb for 182 lncRNAs and precision of 0.8. Additionally, we also annotated lncRNAs with multiple omics annotations, including predicted cis-regulatory TFs, interactions with RBPs, tissue-specific expression profiles, protein co-expression networks, coding potential, sub-cellular localization, and SNPs for ~ 11,000 lncRNAs in the human genome, providing a one-stop dynamic visualization platform. Conclusions Lantern integrates a novel, accurate semi-automatic ontology annotation engine derived annotations combined with a variety of multi-omics annotations for lncRNAs, to provide a central web resource for dissecting the functional dynamics of long non-coding RNAs and to facilitate future hypothesis-driven experiments. The annotation pipeline and a web resource with current annotations for human lncRNAs are freely available on sysbio.lab.iupui.edu/lantern.

scholarly journals In Silico Prediction of Drug–Drug Interactions Mediated by Cytochrome P450 Isoforms

Pharmaceutics ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 538
Author(s):  
Alexander V. Dmitriev ◽  
Anastassia V. Rudik ◽  
Dmitry A. Karasev ◽  
Pavel V. Pogodin ◽  
Alexey A. Lagunin ◽  
...  
Keyword(s):  
Cytochrome P450 ◽  
Drug Interactions ◽  
Cytochromes P450 ◽  
Investigational Drug ◽  
Web Resource ◽  
Average Accuracy ◽  
Structural Formulas ◽  
Cytochrome P450 Isoforms ◽  
Leave One Out ◽  
Important Drug

Drug–drug interactions (DDIs) can cause drug toxicities, reduced pharmacological effects, and adverse drug reactions. Studies aiming to determine the possible DDIs for an investigational drug are part of the drug discovery and development process and include an assessment of the DDIs potential mediated by inhibition or induction of the most important drug-metabolizing cytochrome P450 isoforms. Our study was dedicated to creating a computer model for prediction of the DDIs mediated by the seven most important P450 cytochromes: CYP1A2, CYP2B6, CYP2C19, CYP2C8, CYP2C9, CYP2D6, and CYP3A4. For the creation of structure–activity relationship (SAR) models that predict metabolism-mediated DDIs for pairs of molecules, we applied the Prediction of Activity Spectra for Substances (PASS) software and Pairs of Substances Multilevel Neighborhoods of Atoms (PoSMNA) descriptors calculated based on structural formulas. About 2500 records on DDIs mediated by these cytochromes were used as a training set. Prediction can be carried out both for known drugs and for new, not-yet-synthesized substances. The average accuracy of the prediction of DDIs mediated by various isoforms of cytochrome P450 estimated by leave-one-out cross-validation (LOO CV) procedures was about 0.92. The SAR models created are publicly available as a web resource and provide predictions of DDIs mediated by the most important cytochromes P450.

scholarly journals BART Cancer: a web resource for transcriptional regulators in cancer genomes

NAR Cancer ◽  
2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Zachary V Thomas ◽  
Zhenjia Wang ◽  
Chongzhi Zang
Keyword(s):  
Gene Expression ◽  
Cancer Research ◽  
Computational Prediction ◽  
Transcriptional Regulators ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Regulation Of Transcription ◽  
Data Resource ◽  
Web Resource ◽  
Cancer Types

Abstract Dysregulation of gene expression plays an important role in cancer development. Identifying transcriptional regulators, including transcription factors and chromatin regulators, that drive the oncogenic gene expression program is a critical task in cancer research. Genomic profiles of active transcriptional regulators from primary cancer samples are limited in the public domain. Here we present BART Cancer (bartcancer.org), an interactive web resource database to display the putative transcriptional regulators that are responsible for differentially regulated genes in 15 different cancer types in The Cancer Genome Atlas (TCGA). BART Cancer integrates over 10000 gene expression profiling RNA-seq datasets from TCGA with over 7000 ChIP-seq datasets from the Cistrome Data Browser database and the Gene Expression Omnibus (GEO). BART Cancer uses Binding Analysis for Regulation of Transcription (BART) for predicting the transcriptional regulators from the differentially expressed genes in cancer samples compared to normal samples. BART Cancer also displays the activities of over 900 transcriptional regulators across cancer types, by integrating computational prediction results from BART and the Cistrome Cancer database. Focusing on transcriptional regulator activities in human cancers, BART Cancer can provide unique insights into epigenetics and transcriptional regulation in cancer, and is a useful data resource for genomics and cancer research communities.

scholarly journals MOSAIC: a chemical-genetic interaction data repository and web resource for exploring chemical modes of action

2017 ◽  
Vol 34 (7) ◽  
pp. 1251-1252 ◽  
Author(s):  
Justin Nelson ◽  
Scott W Simpkins ◽  
Hamid Safizadeh ◽  
Sheena C Li ◽  
Jeff S Piotrowski ◽  
...  
Keyword(s):  
Genetic Interaction ◽  
Data Repository ◽  
Interaction Data ◽  
Chemical Genetic ◽  
Web Resource ◽  
Modes Of Action ◽  
Genetic Interaction Data

Internet marketing tool – SEO-optimization of the enterprise site

2021 ◽  
pp. 84-89
Author(s):  
Ihor Ponomarenko ◽  
Alina Sapian
Keyword(s):  
Search Engine ◽  
Research Methodology ◽  
Internet Marketing ◽  
Target Audience ◽  
Digital Marketing ◽  
The Internet ◽  
Digital Environment ◽  
Important Place ◽  
Search Engine Optimization ◽  
Web Resource

The purpose of this article is to consider issues related to the peculiarities of the use of search engine optimization in the implementation of a comprehensive marketing strategy in the digital environment. Research methodology. The research methodology is system-structural and comparative analyzes (to study the application of search engine optimization in the process of improving the efficiency of the company on the Internet); monograph (the study of various software solutions in the field of digital marketing); eco- nomic analysis (when assessing the effectiveness of the use of SEO in the process of attracting the target audience and its impact on the growth of conversions). The scientific novelty – features of using search engine optimization as an effective tool of digital marketing in modern conditions are revealed. The expediency of using SEO to increase the level of competitiveness of the company on the Internet is proved. A set of Internet marketing measures to strengthen the company’s communications with the target audience in the digital environment is revealed, as well as the role in this structure of search engine optimization is outlined. The expediency of building a semantic core as a basic element of search engine optimization of a company’s web resource and creating preconditions for long-term provision of high positions of the site in search services is proved. The subject of the research is the approach to the possibility of using search engine optimization methods in modern conditions to ensure a highly competitive position of the company and its web resources in the digital space in the long period. Conclusions. The digitalization of business leads to the intensification of the use of various digital marketing tools, among which search engine optimization occupies an important place. SEO-optimization of the company’s website involves the implementation of a set of measures aimed at increasing the place of the re- source in search results. Innovative approaches make it possible to integrate an up-to-date keyword list into important elements of a company’s web resource and to constantly update libraries in order to ensure high search engine rankings. Keywords: audience, Internet marketing, search engine optimization, site, targeted traffic.

Sign in / Sign up

Export Citation Format

Share Document