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Text mining

Mikyung Lee, Zhichao Liu, Ruili Huang, Weida Tong
BACKGROUND: All biological processes are inherently dynamic. Biological systems evolve transiently or sustainably according to sequential time points after perturbation by environment insults, drugs and chemicals. Investigating the temporal behavior of molecular events has been an important subject to understand the underlying mechanisms governing the biological system in response to, such as, drug treatment. The intrinsic complexity of time series data requires appropriate computational algorithms for data interpretation...
October 6, 2016: BMC Bioinformatics
Sujoy Roy, Brandon C Curry, Behrouz Madahian, Ramin Homayouni
BACKGROUND: The amount of scientific information about MicroRNAs (miRNAs) is growing exponentially, making it difficult for researchers to interpret experimental results. In this study, we present an automated text mining approach using Latent Semantic Indexing (LSI) for prioritization, clustering and functional annotation of miRNAs. RESULTS: For approximately 900 human miRNAs indexed in miRBase, text documents were created by concatenating titles and abstracts of MEDLINE citations which refer to the miRNAs...
October 6, 2016: BMC Bioinformatics
Langdong Chen, Diya Lv, Dongyao Wang, Xiaofei Chen, Zhenyu Zhu, Yan Cao, Yifeng Chai
Herbal medicines have long been widely used in the treatment of various complex diseases in China. However, the active constituents and therapeutic mechanisms of many herbal medicines remain undefined. Therefore, the identification of the active components and target proteins in these herbal medicines is a formidable task in herbal medicine research. In this study, we proposed a strategy, which integrates network pharmacology with biomedical analysis and surface plasmon resonance (SPR) to predict the active ingredients and potential targets of herbal medicine Sophora flavescens or Kushen in Chinese, and evaluate its anti-fibrosis activity...
October 18, 2016: Molecular BioSystems
Ji-Long Liu, Miao Zhao
Endometriosis affects 5-10% of women in reproductive age, leading to dysmenorrhea, pelvic pain and infertility; however, our understanding on the pathogenesis of this disease remains incomplete. In the present study, we performed a systematic analysis of endometriosis-related genes using text mining. Taking text mining results as input, we subsequently generated a filtered gene set by computing the likelihood of finding more than expected occurrences for every gene across the disease-centered subset of the PubMed database...
October 13, 2016: Genomics
Renu Vyas, Sanket Bapat, Esha Jain, Muthukumarasamy Karthikeyan, Sanjeev Tambe, Bhaskar D Kulkarni
In order to understand the molecular mechanism underlying any disease, knowledge about the interacting proteins in the disease pathway is essential. The number of revealed protein-protein interactions (PPI) is still very limited compared to the available protein sequences of different organisms. Experiment based high-throughput technologies though provide some data about these interactions, those are often fairly noisy. Computational techniques for predicting protein-protein interactions therefore assume significance...
September 30, 2016: Computational Biology and Chemistry
Simon Kocbek, Lawrence Cavedon, David Martinez, Christopher Bain, Chris Mac Manus, Gholamreza Haffari, Ingrid Zukerman, Karin Verspoor
OBJECTIVE: Text and data mining play an important role in obtaining insights from Health and Hospital Information Systems. This paper presents a text mining system for detecting admissions marked as positive for several diseases: Lung Cancer, Breast Cancer, Colon Cancer, Secondary Malignant Neoplasm of Respiratory and Digestive Organs, Multiple Myeloma and Malignant Plasma Cell Neoplasms, Pneumonia, and Pulmonary Embolism. We specifically examine the effect of linking multiple data sources on text classification performance...
October 11, 2016: Journal of Biomedical Informatics
Marta Maciejewska, Delphine Adam, Loïc Martinet, Aymeric Naômé, Magdalena Całusińska, Philippe Delfosse, Monique Carnol, Hazel A Barton, Marie-Pierre Hayette, Nicolas Smargiasso, Edwin De Pauw, Marc Hanikenne, Denis Baurain, Sébastien Rigali
Moonmilk speleothems of limestone caves host a rich microbiome, among which Actinobacteria represent one of the most abundant phyla. Ancient medical texts reported that moonmilk had therapeutical properties, thereby suggesting that its filamentous endemic actinobacterial population might be a source of natural products useful in human treatment. In this work, a screening approach was undertaken in order to isolate cultivable Actinobacteria from moonmilk of the Grotte des Collemboles in Belgium, to evaluate their taxonomic profile, and to assess their potential in biosynthesis of antimicrobials...
2016: Frontiers in Microbiology
Erinç Gökdeniz, Arzucan Özgür, Reşit Canbeyli
Identifying the relations among different regions of the brain is vital for a better understanding of how the brain functions. While a large number of studies have investigated the neuroanatomical and neurochemical connections among brain structures, their specific findings are found in publications scattered over a large number of years and different types of publications. Text mining techniques have provided the means to extract specific types of information from a large number of publications with the aim of presenting a larger, if not necessarily an exhaustive picture...
2016: Frontiers in Neuroinformatics
Sze Ling Chan, Mun Yee Tham, Siew Har Tan, Celine Loke, Belinda Foo, Yanping Fan, Pei San Ang, Liam R Brunham, Cynthia Sung
The aim of this study was to develop and validate sensitive algorithms to detect hospitalized statin-induced myopathy (SIM) cases from electronic medical records (EMRs). We developed 4 algorithms on a training set of 31,211 patient records from a large tertiary hospital. We determined the performance of these algorithms against manually curated records. The best algorithm used a combination of elevated creatine kinase (>4x upper limit of normal), discharge summary, diagnosis, and absence of statin in discharge medications...
October 5, 2016: Clinical Pharmacology and Therapeutics
Kersten Döring, Björn A Grüning, Kiran K Telukunta, Philippe Thomas, Stefan Günther
Information extraction from biomedical literature is continuously growing in scope and importance. Many tools exist that perform named entity recognition, e.g. of proteins, chemical compounds, and diseases. Furthermore, several approaches deal with the extraction of relations between identified entities. The BioCreative community supports these developments with yearly open challenges, which led to a standardised XML text annotation format called BioC. PubMed provides access to the largest open biomedical literature repository, but there is no unified way of connecting its data to natural language processing tools...
2016: PloS One
Kun Hwang, Jin Pyo Lee, Si Yoon Yoo, Hun Kim
The aim of this study was to determine the relationships between free flap complications and old age or comorbidities. In a PubMed and Scopus search, the search terms (1) free flap OR microvascular anastomosis AND (2) elderly OR old age AND (3) complications OR comorbidity OR co-morbidity were used. Among the 62 full-text articles from 241 abstracts, 31 papers without sufficient content were excluded and 10 mined papers were added. Subsequently, 41 papers were reviewed. Overall complication rates of free flap increased significantly with age (p < 0...
September 9, 2016: Journal of Plastic, Reconstructive & Aesthetic Surgery: JPRAS
Sumit Madan, Sven Hodapp, Philipp Senger, Sam Ansari, Justyna Szostak, Julia Hoeng, Manuel Peitsch, Juliane Fluck
Network-based approaches have become extremely important in systems biology to achieve a better understanding of biological mechanisms. For network representation, the Biological Expression Language (BEL) is well designed to collate findings from the scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a BEL Information Extraction Workflow (BELIEF) was developed. BELIEF provides a web-based curation interface, the BELIEF Dashboard, that incorporates text mining techniques to support the biocurator in the generation of BEL networks...
2016: Database: the Journal of Biological Databases and Curation
Juyoung Song, Tae Min Song, Dong-Chul Seo, Jae Hyun Jin
PURPOSE: To investigate online search activity of suicide-related words in South Korean adolescents through data mining of social media Web sites as the suicide rate in South Korea is one of the highest in the world. METHODS: Out of more than 2.35 billion posts for 2 years from January 1, 2011 to December 31, 2012 on 163 social media Web sites in South Korea, 99,693 suicide-related documents were retrieved by Crawler and analyzed using text mining and opinion mining...
September 29, 2016: Journal of Adolescent Health: Official Publication of the Society for Adolescent Medicine
Daohui Zeng, Jidong Peng, Simon Fong, Yining Qiu, Raymond Wong, Yi-Jen Mon
Sentiment prediction emerged as an important machine learning topic to gain insights from unstructured texts, recently gained popularity in health-care industries. Text mining has long been a fundamental data analytic for sentiment prediction. A popular pre-processing step in text mining is transforming text strings to word vectors which form a high-dimensional sparse matrix. This sparse matrix poses computational challenges to induction of accurate sentiment prediction model. Feature selection has been a popular dimensionality reduction technique that finds a subset of features from all the original features from the sparse matrix, in order to enhance the accuracy of the prediction model...
August 5, 2016: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
Jennifer L Huberty, Jeni Matthews, Jenn Leiferman, Janice Hermer, Joanne Cacciatore
OBJECTIVES: To identify and evaluate intervention studies (ie, experimental study in which the participants undergo some kind of intervention in order to evaluate its impact) that target mental and/or physical health outcomes in women who have experienced stillbirth and to provide specific recommendations for future research and intervention work. METHODS: A librarian conducted an initial search using CINAHL, Cochrane Library, PsycInfo, PubMed, SocIndex, and Web of Knowledge in the spring of 2016...
September 29, 2016: Reproductive Sciences
Zhan Ye, Ahmad P Tafti, Karen Y He, Kai Wang, Max M He
BACKGROUND: Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. RESULTS: In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database...
2016: PloS One
Wei-Ti Chen, Russell Barbour
HIV/AIDS is one of the most urgent and challenging public health issues, especially since it is now considered a chronic disease. In this project, we used text mining techniques to extract meaningful words and word patterns from 45 transcribed in-depth interviews of people living with HIV/AIDS (PLWHA) conducted in Taipei, Beijing, Shanghai, and San Francisco from 2006 to 2013. Text mining analysis can predict whether an emerging field will become a long-lasting source of academic interest or whether it is simply a passing source of interest that will soon disappear...
August 12, 2016: AIDS Care
Magnus Ahltorp, Maria Skeppstedt, Shiho Kitajima, Aron Henriksson, Rafal Rzepka, Kenji Araki
BACKGROUND: Research on medical vocabulary expansion from large corpora has primarily been conducted using text written in English or similar languages, due to a limited availability of large biomedical corpora in most languages. Medical vocabularies are, however, essential also for text mining from corpora written in other languages than English and belonging to a variety of medical genres. The aim of this study was therefore to evaluate medical vocabulary expansion using a corpus very different from those previously used, in terms of grammar and orthographics, as well as in terms of text genre...
September 26, 2016: Journal of Biomedical Semantics
Farnoush Pedrami, Pamela Asenso, Sachin Devi
Objective. To identify trends in pharmacy education during last two decades using text mining. Methods. Articles published in the American Journal of Pharmaceutical Education (AJPE) in the past two decades were compiled in a database. Custom text analytics software was written using Visual Basic programming language in the Visual Basic for Applications (VBA) editor of Excel 2007. Frequency of words appearing in article titles was calculated using the custom VBA software. Data were analyzed to identify the emerging trends in pharmacy education...
August 25, 2016: American Journal of Pharmaceutical Education
Pier Luigi Buttigieg, Evangelos Pafilis, Suzanna E Lewis, Mark P Schildhauer, Ramona L Walls, Christopher J Mungall
BACKGROUND: The Environment Ontology (ENVO; ), first described in 2013, is a resource and research target for the semantically controlled description of environmental entities. The ontology's initial aim was the representation of the biomes, environmental features, and environmental materials pertinent to genomic and microbiome-related investigations. However, the need for environmental semantics is common to a multitude of fields, and ENVO's use has steadily grown since its initial description...
2016: Journal of Biomedical Semantics
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