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https://www.readbyqxmd.com/read/28915268/large-scale-cross-species-chemogenomic-platform-proposes-a-new-drug-discovery-strategy-of-veterinary-drug-from-herbal-medicines
#1
Chao Huang, Yang Yang, Xuetong Chen, Chao Wang, Yan Li, Chunli Zheng, Yonghua Wang
Veterinary Herbal Medicine (VHM) is a comprehensive, current, and informative discipline on the utilization of herbs in veterinary practice. Driven by chemistry but progressively directed by pharmacology and the clinical sciences, drug research has contributed more to address the needs for innovative veterinary medicine for curing animal diseases. However, research into veterinary medicine of vegetal origin in the pharmaceutical industry has reduced, owing to questions such as the short of compatibility of traditional natural-product extract libraries with high-throughput screening...
2017: PloS One
https://www.readbyqxmd.com/read/28913827/when-more-is-less-an-exploratory-study-of-the-precautionary-reporting-bias-and-its-impact-on-safety-signal-detection
#2
Kevin Klein, Joep Hg Scholl, Marie L De Bruin, Eugène P van Puijenbroek, Hubert Gm Leufkens, Pieter Stolk
Concerns have been expressed that large numbers of non-value added reports have been accumulating in ADR databases, for example via patient support programs. We performed an assessment of the impact of such reports, to which we refer to as 'precautionary reports', on safety signal detection in the Netherlands. The case narratives of ADR reports of three case products were screened with text-mining algorithms to identify those reports that lack a causal relationship with the suspected medicinal product. We demonstrate that precautionary reports impede the optimal use of the pharmacovigilance system by, on the one hand, masking safety signals and, on the other hand, creating spurious signals...
September 15, 2017: Clinical Pharmacology and Therapeutics
https://www.readbyqxmd.com/read/28894735/navigating-the-functional-landscape-of-transcription-factors-via-non-negative-tensor-factorization-analysis-of-medline-abstracts
#3
Sujoy Roy, Daqing Yun, Behrouz Madahian, Michael W Berry, Lih-Yuan Deng, Daniel Goldowitz, Ramin Homayouni
In this study, we developed and evaluated a novel text-mining approach, using non-negative tensor factorization (NTF), to simultaneously extract and functionally annotate transcriptional modules consisting of sets of genes, transcription factors (TFs), and terms from MEDLINE abstracts. A sparse 3-mode term × gene × TF tensor was constructed that contained weighted frequencies of 106,895 terms in 26,781 abstracts shared among 7,695 genes and 994 TFs. The tensor was decomposed into sub-tensors using non-negative tensor factorization (NTF) across 16 different approximation ranks...
2017: Frontiers in Bioengineering and Biotechnology
https://www.readbyqxmd.com/read/28881963/deep-learning-with-word-embeddings-improves-biomedical-named-entity-recognition
#4
Maryam Habibi, Leon Weber, Mariana Neves, David Luis Wiegandt, Ulf Leser
Motivation: Text mining has become an important tool for biomedical research. The most fundamental text-mining task is the recognition of biomedical named entities (NER), such as genes, chemicals and diseases. Current NER methods rely on pre-defined features which try to capture the specific surface properties of entity types, properties of the typical local context, background knowledge, and linguistic information. State-of-the-art tools are entity-specific, as dictionaries and empirically optimal feature sets differ between entity types, which makes their development costly...
July 15, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28880689/prodromal-signs-and-symptoms-of-serious-infections-with-tocilizumab-treatment-for-rheumatoid-arthritis-text-mining-of-the-japanese-postmarketing-adverse-event-reporting-database
#5
Tatsuya Atsumi, Yoshiaki Ando, Shinichi Matsuda, Shiho Tomizawa, Riwa Tanaka, Nobuhiro Takagi, Ayako Nakasone
OBJECTIVE: To search for signs and symptoms before serious infection (SI) occurs in tocilizumab (TCZ)-treated rheumatoid arthritis (RA) patients. METHODS: Individual case safety reports, including structured (age, sex, adverse event [AE]) and unstructured (clinical narratives) data, were analyzed by automated text mining from a Japanese post-marketing AE-reporting database (16 April 2008-10 April 2015) assuming the following: treated in Japan; TCZ RA treatment; ≥1 SI; unable to exclude causality between TCZ and SIs...
September 7, 2017: Modern Rheumatology
https://www.readbyqxmd.com/read/28875065/biofueldb-a-database-and-prediction-server-of-enzymes-involved-in-biofuels-production
#6
Nikhil Chaudhary, Ankit Gupta, Sudheer Gupta, Vineet K Sharma
BACKGROUND: In light of the rapid decrease in fossils fuel reserves and an increasing demand for energy, novel methods are required to explore alternative biofuel production processes to alleviate these pressures. A wide variety of molecules which can either be used as biofuels or as biofuel precursors are produced using microbial enzymes. However, the common challenges in the industrial implementation of enzyme catalysis for biofuel production are the unavailability of a comprehensive biofuel enzyme resource, low efficiency of known enzymes, and limited availability of enzymes which can function under extreme conditions in the industrial processes...
2017: PeerJ
https://www.readbyqxmd.com/read/28875048/text-mining-in-biomedical-domain-with-emphasis-on-document-clustering
#7
REVIEW
Vinaitheerthan Renganathan
OBJECTIVES: With the exponential increase in the number of articles published every year in the biomedical domain, there is a need to build automated systems to extract unknown information from the articles published. Text mining techniques enable the extraction of unknown knowledge from unstructured documents. METHODS: This paper reviews text mining processes in detail and the software tools available to carry out text mining. It also reviews the roles and applications of text mining in the biomedical domain...
July 2017: Healthcare Informatics Research
https://www.readbyqxmd.com/read/28871390/exploring-sets-of-molecules-from-patents-and-relationships-to-other-active-compounds-in-chemical-space-networks
#8
Ryo Kunimoto, Jürgen Bajorath
Patents from medicinal chemistry represent a rich source of novel compounds and activity data that appear only infrequently in the scientific literature. Moreover, patent information provides a primary focal point for drug discovery. Accordingly, text mining and image extraction approaches have become hot topics in patent analysis and repositories of patent data are being established. In this work, we have generated network representations using alternative similarity measures to systematically compare molecules from patents with other bioactive compounds, visualize similarity relationships, explore the chemical neighbourhood of patent molecules, and identify closely related compounds with different activities...
September 4, 2017: Journal of Computer-aided Molecular Design
https://www.readbyqxmd.com/read/28865927/construction-accident-narrative-classification-an-evaluation-of-text-mining-techniques
#9
Yang Miang Goh, C U Ubeynarayana
Learning from past accidents is fundamental to accident prevention. Thus, accident and near miss reporting are encouraged by organizations and regulators. However, for organizations managing large safety databases, the time taken to accurately classify accident and near miss narratives will be very significant. This study aims to evaluate the utility of various text mining classification techniques in classifying 1000 publicly available construction accident narratives obtained from the US OSHA website. The study evaluated six machine learning algorithms, including support vector machine (SVM), linear regression (LR), random forest (RF), k-nearest neighbor (KNN), decision tree (DT) and Naive Bayes (NB), and found that SVM produced the best performance in classifying the test set of 251 cases...
August 31, 2017: Accident; Analysis and Prevention
https://www.readbyqxmd.com/read/28858819/machine-learning-approaches-on-diagnostic-term-encoding-with-the-icd-for-clinical-documentation
#10
Aitziber Atutxa, Alicia Perez, Arantza Casillas
This work focuses on data mining applied to the clinical documentation domain. Diagnostic Terms (DTs) are used as keywords to retrieve valuable information from Electronic Health Records (EHRs). Indeed, they are encoded manually by experts following the International Classification of Diseases (ICD). The goal of this work is to explore the aid of text mining on DT encoding. From the machine learning (ML) perspective, this is a high-dimensional classification task, as it comprises thousands of codes. This work delves into a robust representation of the instances to improve ML results...
August 24, 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28845458/paperblast-text-mining-papers-for-information-about-homologs
#11
Morgan N Price, Adam P Arkin
Large-scale genome sequencing has identified millions of protein-coding genes whose function is unknown. Many of these proteins are similar to characterized proteins from other organisms, but much of this information is missing from annotation databases and is hidden in the scientific literature. To make this information accessible, PaperBLAST uses EuropePMC to search the full text of scientific articles for references to genes. PaperBLAST also takes advantage of curated resources (Swiss-Prot, GeneRIF, and EcoCyc) that link protein sequences to scientific articles...
July 2017: MSystems
https://www.readbyqxmd.com/read/28842730/evidence-based-prioritisation-and-enrichment-of-genes-interacting-with-metformin-in-type-2-diabetes
#12
Adem Y Dawed, Ashfaq Ali, Kaixin Zhou, Ewan R Pearson, Paul W Franks
AIMS/HYPOTHESIS: There is an extensive body of literature suggesting the involvement of multiple loci in regulating the action of metformin; most findings lack replication, without which distinguishing true-positive from false-positive findings is difficult. To address this, we undertook evidence-based, multiple data integration to determine the validity of published evidence. METHODS: We (1) built a database of published data on gene-metformin interactions using an automated text-mining approach (n = 5963 publications), (2) generated evidence scores for each reported locus, (3) from which a rank-ordered gene set was generated, and (4) determined the extent to which this gene set was enriched for glycaemic response through replication analyses in a well-powered independent genome-wide association study (GWAS) dataset from the Genetics of Diabetes and Audit Research Tayside Study (GoDARTS)...
August 25, 2017: Diabetologia
https://www.readbyqxmd.com/read/28838071/informatics-support-for-basic-research-in-biomedicine
#13
Thomas C Rindflesch, Catherine L Blake, Marcelo Fiszman, Halil Kilicoglu, Graciela Rosemblat, Jodi Schneider, Caroline J Zeiss
Informatics methodologies exploit computer-assisted techniques to help biomedical researchers manage large amounts of information. In this paper, we focus on the biomedical research literature (MEDLINE). We first provide an overview of some text mining techniques that offer assistance in research by identifying biomedical entities (e.g., genes, substances, and diseases) and relations between them in text.We then discuss Semantic MEDLINE, an application that integrates PubMed document retrieval, concept and relation identification, and visualization, thus enabling a user to explore concepts and relations from within a set of retrieved citations...
July 1, 2017: ILAR Journal
https://www.readbyqxmd.com/read/28830417/empirical-advances-with-text-mining-of-electronic-health-records
#14
T Delespierre, P Denormandie, A Bar-Hen, L Josseran
BACKGROUND: Korian is a private group specializing in medical accommodations for elderly and dependent people. A professional data warehouse (DWH) established in 2010 hosts all of the residents' data. Inside this information system (IS), clinical narratives (CNs) were used only by medical staff as a residents' care linking tool. The objective of this study was to show that, through qualitative and quantitative textual analysis of a relatively small physiotherapy and well-defined CN sample, it was possible to build a physiotherapy corpus and, through this process, generate a new body of knowledge by adding relevant information to describe the residents' care and lives...
August 22, 2017: BMC Medical Informatics and Decision Making
https://www.readbyqxmd.com/read/28829362/content-analysis-of-student-essays-after-attending-a-problem-based-learning-course-facilitating-the-development-of-critical-thinking-and-communication-skills-in-japanese-nursing-students
#15
Tomoya Itatani, Kyoko Nagata, Kiyoko Yanagihara, Noriko Tabuchi
The importance of active learning has continued to increase in Japan. The authors conducted classes for first-year students who entered the nursing program using the problem-based learning method which is a kind of active learning. Students discussed social topics in classes. The purposes of this study were to analyze the post-class essay, describe logical and critical thinking after attended a Problem-Based Learning (PBL) course. The authors used Mayring's methodology for qualitative content analysis and text mining...
August 22, 2017: Healthcare (Basel, Switzerland)
https://www.readbyqxmd.com/read/28822857/exploring-associations-of-clinical-and-social-parameters-with-violent-behaviors-among-psychiatric-patients
#16
Hong-Jie Dai, Emily Chia-Yu Su, Mohy Uddin, Jitendra Jonnagaddala, Chi-Shin Wu, Shabbir Syed-Abdul
Evidence has revealed interesting associations of clinical and social parameters with violent behaviors of patients with psychiatric disorders. Men are more violent preceding and during hospitalization, whereas women are more violent than men throughout the 3days following a hospital admission. It has also been proven that mental disorders may be a consistent risk factor for the occurrence of violence. In order to better understand violent behaviors of patients with psychiatric disorders, it is important to investigate both the clinical symptoms and psychosocial factors that accompany violence in these patients...
August 16, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28816337/a-bag-of-concepts-approach-for-biomedical-document-classification-using-wikipedia-knowledge-spanish-english-cross-language-case-study
#17
Marcos A Mouriño-García, Roberto Pérez-Rodríguez, Luis E Anido-Rifón
OBJECTIVES: The ability to efficiently review the existing literature is essential for the rapid progress of research. This paper describes a classifier of text documents, represented as vectors in spaces of Wikipedia concepts, and analyses its suitability for classification of Spanish biomedical documents when only English documents are available for training. We propose the cross-language concept matching (CLCM) technique, which relies on Wikipedia interlanguage links to convert concept vectors from the Spanish to the English space...
August 16, 2017: Methods of Information in Medicine
https://www.readbyqxmd.com/read/28815149/classifying-supplement-use-status-in-clinical-notes
#18
Yadan Fan, Lu He, Serguei V S Pakhomov, Genevieve B Melton, Rui Zhang
Clinical notes contain rich information about supplement use that is critical for detecting adverse interactions between supplements and prescribed medications. It is important to know the context in which supplements are mentioned in clinical notes to be able to correctly identify patients that either currently take the supplement or did so in the past. We applied text mining methods to automatically classify supplement use into four status categories: Continuing (C), Discontinued (D), Started (S), and Unclassified (U)...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815133/correlating-lab-test-results-in-clinical-notes-with-structured-lab-data-a-case-study-in-hba1c-and-glucose
#19
Liu Sijia, Wang Liwei, Donna Ihrke, Vipin Chaudhary, Cui Tao, Chunhua Weng, Hongfang Liu
It is widely acknowledged that information extraction of unstructured clinical notes using natural language processing (NLP) and text mining is essential for secondary use of clinical data for clinical research and practice. Lab test results are currently structured in most of the electronic health record (EHR) systems. However, for referral patients or lab tests that can be done in non-clinical setting, the results can be captured in unstructured clinical notes. In this study, we proposed a rule-based information extraction system to extract the lab test results with temporal information from clinical notes...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815126/a-simple-text-mining-approach-for-ranking-pairwise-associations-in-biomedical-applications
#20
Finn Kuusisto, John Steill, Zhaobin Kuang, James Thomson, David Page, Ron Stewart
We present a simple text mining method that is easy to implement, requires minimal data collection and preparation, and is easy to use for proposing ranked associations between a list of target terms and a key phrase. We call this method KinderMiner, and apply it to two biomedical applications. The first application is to identify relevant transcription factors for cell reprogramming, and the second is to identify potential drugs for investigation in drug repositioning. We compare the results from our algorithm to existing data and state-of-the-art algorithms, demonstrating compelling results for both application areas...
2017: AMIA Summits on Translational Science Proceedings
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