scholarly journals Vapur: A Search Engine to Find Related Protein - Compound Pairs in COVID-19 Literature

2020 ◽  
Author(s):  
Abdullatif Köksal ◽  
Hilal Dönmez ◽  
Rıza Özçelik ◽  
Elif Ozkirimli ◽  
Arzucan Özgür
Keyword(s):  
User Interface ◽  
Search Engine ◽  
Current Literature ◽  
Search Engines ◽  
General Purpose ◽  
Inverted Index ◽  
Related Protein ◽  
Domain Specific ◽  
Link Type

AbstractCoronavirus Disease of 2019 (COVID-19) created dire consequences globally and triggered an intense scientific effort from different domains. The resulting publications created a huge text collection in which finding the studies related to a biomolecule of interest is challenging for general purpose search engines because the publications are rich in domain specific terminology. Here, we present Vapur: an online COVID-19 search engine specifically designed to find related protein - chemical pairs. Vapur is empowered with a relation-oriented inverted index that is able to retrieve and group studies for a query biomolecule with respect to its related entities. The inverted index of Vapur is automatically created with a BioNLP pipeline and integrated with an online user interface. The online interface is designed for the smooth traversal of the current literature by domain researchers and is publicly available at https://tabilab.cmpe.boun.edu.tr/vapur/.

Towards Improving Meta-Search through Exploiting an Integrated Search Model

2011 ◽  
Vol 10 (04) ◽  
pp. 379-391
Author(s):  
Mohammed Maree ◽  
Saadat M. Alhashmi ◽  
Mohammed Belkhatir
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
General Purpose ◽  
Search Model ◽  
Domain Specific ◽  
Meta Search Engine ◽  
Meta Search ◽  
Results Merging ◽  
Multiple Domain

Meta-search engines are created to reduce the burden on the user by dispatching queries to multiple search engines in parallel. Decisions on how to rank the returned results are made based on the query's keywords. Although keyword-based search model produces good results, better results can be obtained by integrating semantic and statistical based relatedness measures into this model. Such integration allows the meta-search engine to search by meanings rather than only by literal strings. In this article, we present Multi-Search+, the next generation of Multi-Search general-purpose meta-search engine. The extended version of the system employs additional knowledge represented by multiple domain-specific ontologies to enhance both the query processing and the returned results merging. In addition, new general-purpose search engines are plugged-in to its architecture. Experimental results demonstrate that our integrated search model obtained significant improvement in the quality of the produced search results.

scholarly journals Microbiome Search Engine 2: a Platform for Taxonomic and Functional Search of Global Microbiomes on the Whole-Microbiome Level

mSystems ◽  
2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Gongchao Jing ◽  
Lu Liu ◽  
Zengbin Wang ◽  
Yufeng Zhang ◽  
Li Qian ◽  
...  
Keyword(s):  
Big Data ◽  
User Interface ◽  
Search Engine ◽  
Functional Similarity ◽  
Metagenomic Data ◽  
Data Sets ◽  
Data Space ◽  
Link Type ◽  
Database Platform ◽  
Microbiome Data

ABSTRACT Metagenomic data sets from diverse environments have been growing rapidly. To ensure accessibility and reusability, tools that quickly and informatively correlate new microbiomes with existing ones are in demand. Here, we introduce Microbiome Search Engine 2 (MSE 2), a microbiome database platform for searching query microbiomes in the global metagenome data space based on the taxonomic or functional similarity of a whole microbiome to those in the database. MSE 2 consists of (i) a well-organized and regularly updated microbiome database that currently contains over 250,000 metagenomic shotgun and 16S rRNA gene amplicon samples associated with unified metadata collected from 798 studies, (ii) an enhanced search engine that enables real-time and fast (<0.5 s per query) searches against the entire database for best-matched microbiomes using overall taxonomic or functional profiles, and (iii) a Web-based graphical user interface for user-friendly searching, data browsing, and tutoring. MSE 2 is freely accessible via http://mse.ac.cn. For standalone searches of customized microbiome databases, the kernel of the MSE 2 search engine is provided at GitHub (https://github.com/qibebt-bioinfo/meta-storms). IMPORTANCE A search-based strategy is useful for large-scale mining of microbiome data sets, such as a bird’s-eye view of the microbiome data space and disease diagnosis via microbiome big data. Here, we introduce Microbiome Search Engine 2 (MSE 2), a microbiome database platform for searching query microbiomes against the existing microbiome data sets on the basis of their similarity in taxonomic structure or functional profile. Key improvements include database extension, data compatibility, a search engine kernel, and a user interface. The new ability to search the microbiome space via functional similarity greatly expands the scope of search-based mining of the microbiome big data.

Web Usage Mining in Search Engines

Web Mining ◽  
2011 ◽  
pp. 307-321 ◽  
Author(s):  
Ricardo Baeza-Yates
Keyword(s):  
User Interface ◽  
Search Engine ◽  
Power Law ◽  
Search Engines ◽  
Real Data ◽  
Web Usage Mining ◽  
Power Law Distribution ◽  
Main Ideas ◽  
Answer Ranking ◽  
Navigation Information

Search engine logs not only keep navigation information, but also the queries made by their users. In particular, queries to a search engine follow a power-law distribution, which is far from uniform. Queries and related clicks can be used to improve the search engine itself in different aspects: user interface, index performance, and answer ranking. In this chapter we present some of the main ideas proposed in query mining and we show a few examples based on real data from a search engine focused on the Chilean Web.

Web Search Engine Architectures and their Performance Analysis

2011 ◽  
pp. 491-509
Author(s):  
Xiannong Meng
Keyword(s):  
Performance Analysis ◽  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
General Purpose ◽  
Performance Measurements ◽  
Web Documents ◽  
System Architectures ◽  
Web Search Engine ◽  
And Performance

This chapter surveys various technologies involved in a Web search engine with an emphasis on performance analysis issues. The aspects of a general-purpose search engine covered in this survey include system architectures, information retrieval theories as the basis of Web search, indexing and ranking of Web documents, relevance feedback and machine learning, personalization, and performance measurements. The objectives of the chapter are to review the theories and technologies pertaining to Web search, and help us understand how Web search engines work and how to use the search engines more effectively and efficiently.

CASONTO

2016 ◽  
Vol 12 (2) ◽  
pp. 242-262 ◽  
Author(s):  
Awny Sayed ◽  
Amal Al Muqrishi
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Question Answering ◽  
Arabic Language ◽  
Semantic Search ◽  
Specific Domain ◽  
Content Type ◽  
Entity Search ◽  
Domain Specific ◽  
Semantic Search Engine

Purpose The purpose of this paper is to present an efficient and scalable Arabic semantic search engine based on a domain-specific ontological graph for Colleges of Applied Science, Sultanate of Oman (CASOnto). It also supports the factorial question answering and uses two types of searching: the keyword-based search and the semantics-based search in both languages Arabic and English. This engine is built on variety of technologies such as resource description framework data and ontological graph. Furthermore, two experimental results are conducted; the first is a comparison among entity-search and the classical-search in the system itself. The second compares the CASOnto with well-known semantic search engines such as Kngine, Wolfram Alpha and Google to measure their performance and efficiency. Design/methodology/approach The design and implementation of the system comprises the following phases, namely, designing inference, storing, indexing, searching, query processing and the user’s friendly interface, where it is designed based on a specific domain of the IBRI CAS (College of Applied Science) to highlight the academic and nonacademic departments. Furthermore, it is ontological inferred data stored in the tuple data base (TDB) and MySQL to handle the keyword-based search as well as entity-based search. The indexing and searching processes are built based on the Lucene for the keyword search, while TDB is used for the entity search. Query processing is a very important component in the search engines that helps to improve the user’s search results and make the system efficient and scalable. CASOnto handles the Arabic issues such as spelling correction, query completion, stop words’ removal and diacritics removal. It also supports the analysis of the factorial question answering. Findings In this paper, an efficient and scalable Arabic semantic search engine is proposed. The results show that the semantic search that built on the SPARQL is better than the classical search in both simple and complex queries. Clearly, the accuracy of semantic search equals to 100 per cent in both types of queries. On the other hand, the comparison of CASOnto with the Wolfram Alpha, Kngine and Google refers to better results by CASOnto. Consequently, it seems that our proposed engine retrieved better and efficient results than other engines. Thus, it is built according to the ontological domain-specific, highly scalable performance and handles the complex queries well by understanding the context behind the query. Research limitations/implications The proposed engine is built on a specific domain (CAS Ibri – Oman), and in the future vision, it will highlight the nonfactorial question answering and expand the domain of CASOnto to involve more integrated different domains. Originality/value The main contribution of this paper is to build an efficient and scalable Arabic semantic search engine. Because of the widespread use of search engines, a new dimension of challenge is created to keep up with the evolution of the semantic Web. Whereas, catering to the needs of users has become a matter of paramount importance in the light of artificial intelligence and technological development to access the accurate and the efficient information in less possible time. However, the research challenges still in its infancy due to lack of research engine that supports the Arabic language. It could be traced back to the complexity of the Arabic language morphological and grammar rules.

A New Approach for Building a Scalable and Adaptive Vertical Search Engine

2010 ◽  
pp. 159-187
Author(s):  
H. Arafat Ali ◽  
Ali I. El Desouky ◽  
Ahmed I. Saleh
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
General Purpose ◽  
Specific Domain ◽  
Vertical Search ◽  
Vertical Search Engine ◽  
Focused Crawlers ◽  
New Generation ◽  
Adaptation Ability ◽  
The Web

Search engines are the most important search tools for finding useful and recent information on the Web today. They rely on crawlers that continually crawl the Web for new pages. Meanwhile, focused crawlers have become an attractive area for research in recent years. They suggest a better solution for general-purpose search engine limitations and lead to a new generation of search engines called vertical-search engines. Searching the Web vertically is to divide the Web into smaller regions; each region is related to a specific domain. In addition, one crawler is allowed to search in each domain. The innovation of this article is adding intelligence and adaptation ability to focused crawlers. Such added features will certainly guide the crawler perfectly to retrieve more relevant pages while crawling the Web. The proposed crawler has the ability to estimate the rank of the page before visiting it and adapts itself to any changes in its domain using.

scholarly journals Bystro: rapid online variant annotation and natural-language filtering at whole-genome scale

2017 ◽  
Author(s):  
Alex V. Kotlar ◽  
Cristina E. Trevino ◽  
Michael E. Zwick ◽  
David J. Cutler ◽  
Thomas S. Wingo
Keyword(s):  
Natural Language ◽  
Search Engine ◽  
Processing Time ◽  
General Purpose ◽  
Whole Genome ◽  
Command Line ◽  
Variant Annotation ◽  
Link Type ◽  
Key Innovation ◽  
Genome Scale

AbstractAccurately selecting relevant alleles in large sequencing experiments remains technically challenging. Bystro (https://bystro.io/) is the first online, cloud-based application that makes variant annotation and filtering accessible to all researchers for terabyte-sized whole-genome experiments containing thousands of samples. Its key innovation is a general-purpose, natural-language search engine that enables users to identify and export alleles and samples of interest in milliseconds. The search engine dramatically simplifies complex filtering tasks that previously required programming experience or specialty command-line programs. Critically, Bystro’s annotation and filtering capabilities are orders of magnitude faster than previous solutions, saving weeks of processing time for large experiments.

scholarly journals AB1346-HPR REAL-WORLD EFFECTIVENESS AND PERCEIVED USEFULNESS OF SYMPTOM CHECKERS IN RHEUMATOLOGY: INTERIM REPORT FROM THE PROSPECTIVE MULTICENTER BETTER STUDY

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1961.1-1961
Author(s):  
J. Knitza ◽  
J. Mohn ◽  
C. Bergmann ◽  
E. Kampylafka ◽  
M. Hagen ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Real World ◽  
Search Engines ◽  
Correct Diagnosis ◽  
Perceived Usefulness ◽  
Symptom Duration ◽  
Research Support ◽  
Link Type ◽  
The Mean ◽  
Research Grant

Background:Symptom checkers (SC) promise to reduce diagnostic delay, misdiagnosis and effectively guide patients through healthcare systems. They are increasingly used, however little evidence exists about their real-life effectiveness.Objectives:The aim of this study was to evaluate the diagnostic accuracy, usage time, usability and perceived usefulness of two promising SC, ADA (www.ada.com) and Rheport (www.rheport.de). Furthermore, symptom duration and previous symptom checking was recorded.Methods:Cross-sectional interim clinical data from the first of three recruiting centers from the prospective, real-world, multicenter bETTeR-study (DKRS DRKS00017642) was used. Patients newly presenting to a secondary rheumatology outpatient clinic between September and December 2019 completed the ADA and Rheport SC. The time and answers were recorded and compared to the patient’s actual diagnosis. ADA provides up to 5 disease suggestions, Rheport calculates a risk score for rheumatic musculoskeletal diseases (RMDs) (≥1=RMD). For both SC the sensitivity, specificity was calculated regarding RMDs. Furthermore, patients completed a survey evaluating the SC usability using the system usability scale (SUS), perceived usefulness, previous symptom checking and symptom duration.Results:Of the 129 consecutive patients approached, 97 agreed to participate. 38% (37/97) of the presenting patients presented with an RMD (Figure 1). Mean symptom duration was 146 weeks and a mean number of 10 physician contacts occurred previously, to evaluate current symptoms. 56% (54/96) had previously checked their symptoms on the internet using search engines, spending a mean of 6 hours. Rheport showed a sensitivity of 49% (18/37) and specificity of 58% (35/60) concerning RMDs. ADA’s top 1 and top 5 disease suggestions concerning RMD showed a sensitivity of 43% (16/37) and 54% (20/37) and a specificity of 58% (35/60) and 52% (31/60), respectively. ADA listed the correct diagnosis of the patients with RMDs first or within the first 5 disease suggestions in 19% (7/37) and 30% (11/37), respectively. The average perceived usefulness for checking symptoms using ADA, internet search engines and Rheport was 3.0, 3.5 and 3.1 on a visual analog scale from 1-5 (5=very useful). 61% (59/96) and 64% (61/96) would recommend using ADA and Rheport, respectively. The mean SUS score of ADA and Rheport was 72/100 and 73/100. The mean usage time for ADA and Rheport was 8 and 9 minutes, respectively.Conclusion:This is the first prospective, real-world, multicenter study evaluating the diagnostic accuracy and other features of two currently used SC in rheumatology. These interim results suggest that diagnostic accuracy is limited, however SC are well accepted among patients and in some cases, correct diagnosis can be provided out of the pocket within few minutes, saving valuable time.Figure:Acknowledgments:This study was supported by an unrestricted research grant from Novartis.Disclosure of Interests:Johannes Knitza Grant/research support from: Research Grant: Novartis, Jacob Mohn: None declared, Christina Bergmann: None declared, Eleni Kampylafka Speakers bureau: Novartis, BMS, Janssen, Melanie Hagen: None declared, Daniela Bohr: None declared, Elizabeth Araujo Speakers bureau: Novartis, Lilly, Abbott, Matthias Englbrecht Grant/research support from: Roche Pharma, Chugai Pharma Europe, Consultant of: AbbVie, Roche Pharma, RheumaDatenRhePort GbR, Speakers bureau: AbbVie, Celgene, Chugai Pharma Europe, Lilly, Mundipharma, Novartis, Pfizer, Roche Pharma, UCB, David Simon Grant/research support from: Else Kröner-Memorial Scholarship, Novartis, Consultant of: Novartis, Lilly, Arnd Kleyer Consultant of: Lilly, Gilead, Novartis,Abbvie, Speakers bureau: Novartis, Lilly, Timo Meinderink: None declared, Wolfgang Vorbrüggen: None declared, Cay-Benedict von der Decken: None declared, Stefan Kleinert Shareholder of: Morphosys, Grant/research support from: Novartis, Consultant of: Novartis, Speakers bureau: Abbvie, Novartis, Celgene, Roche, Chugai, Janssen, Andreas Ramming Grant/research support from: Pfizer, Novartis, Consultant of: Boehringer Ingelheim, Novartis, Gilead, Pfizer, Speakers bureau: Boehringer Ingelheim, Roche, Janssen, Jörg Distler Grant/research support from: Boehringer Ingelheim, Consultant of: Boehringer Ingelheim, Paid instructor for: Boehringer Ingelheim, Speakers bureau: Boehringer Ingelheim, Peter Bartz-Bazzanella: None declared, Georg Schett Speakers bureau: AbbVie, BMS, Celgene, Janssen, Eli Lilly, Novartis, Roche and UCB, Axel Hueber Grant/research support from: Novartis, Lilly, Pfizer, Consultant of: Abbvie, BMS, Celgene, Gilead, GSK, Lilly, Novartis, Speakers bureau: GSK, Lilly, Novartis, Martin Welcker Grant/research support from: Abbvie, Novartis, UCB, Hexal, BMS, Lilly, Roche, Celgene, Sanofi, Consultant of: Abbvie, Actelion, Aescu, Amgen, Celgene, Hexal, Janssen, Medac, Novartis, Pfizer, Sanofi, UCB, Speakers bureau: Abbvie, Aescu, Amgen, Biogen, Berlin Chemie, Celgene, GSK, Hexal, Mylan, Novartis, Pfizer, UCB

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