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https://www.readbyqxmd.com/read/28817730/new-approach-to-generating-insights-for-aging-research-based-on-literature-mining-and-knowledge-integration
#1
Yeondae Kwon, Yukikazu Natori, Masaru Tanokura
The proportion of the elderly population in most countries worldwide is increasing dramatically. Therefore, social interest in the fields of health, longevity, and anti-aging has been increasing as well. However, the basic research results obtained from a reductionist approach in biology and a bioinformatic approach in genome science have limited usefulness for generating insights on future health, longevity, and anti-aging-related research on a case by case basis. We propose a new approach that uses our literature mining technique and bioinformatics, which lead to a better perspective on research trends by providing an expanded knowledge base to work from...
2017: PloS One
https://www.readbyqxmd.com/read/28817654/investigating-spousal-concordance-of-diabetes-through-statistical-analysis-and-data-mining
#2
Jong-Yi Wang, Chiu-Shong Liu, Chi-Hsuan Lung, Ya-Tun Yang, Ming-Hung Lin
OBJECTIVE: Spousal clustering of diabetes merits attention. Whether old-age vulnerability or a shared family environment determines the concordance of diabetes is also uncertain. This study investigated the spousal concordance of diabetes and compared the risk of diabetes concordance between couples and noncouples by using nationally representative data. METHODS: A total of 22,572 individuals identified from the 2002-2013 National Health Insurance Research Database of Taiwan constituted 5,643 couples and 5,643 noncouples through 1:1 dual propensity score matching (PSM)...
2017: PloS One
https://www.readbyqxmd.com/read/28817602/exploring-the-potential-of-a-structural-alphabet-based-tool-for-mining-multiple-target-conformations-and-target-flexibility-insight
#3
Leslie Regad, Jean-Baptiste Chéron, Dhoha Triki, Caroline Senac, Delphine Flatters, Anne-Claude Camproux
Protein flexibility is often implied in binding with different partners and is essential for protein function. The growing number of macromolecular structures in the Protein Data Bank entries and their redundancy has become a major source of structural knowledge of the protein universe. The analysis of structural variability through available redundant structures of a target, called multiple target conformations (MTC), obtained using experimental or modeling methods and under different biological conditions or different sources is one way to explore protein flexibility...
2017: PloS One
https://www.readbyqxmd.com/read/28817592/using-k-dependence-causal-forest-to-mine-the-most-significant-dependency-relationships-among-clinical-variables-for-thyroid-disease-diagnosis
#4
LiMin Wang, FangYuan Cao, ShuangCheng Wang, MingHui Sun, LiYan Dong
Numerous data mining models have been proposed to construct computer-aided medical expert systems. Bayesian network classifiers (BNCs) are more distinct and understandable than other models. To graphically describe the dependency relationships among clinical variables for thyroid disease diagnosis and ensure the rationality of the diagnosis results, the proposed k-dependence causal forest (KCF) model generates a series of submodels in the framework of maximum spanning tree (MST) and demonstrates stronger dependence representation...
2017: PloS One
https://www.readbyqxmd.com/read/28816067/post-acquisition-data-mining-techniques-for-lc-ms-ms-acquired-data-in-drug-metabolite-identification
#5
Pooja Sukhdev Dhurjad, Vamsi Krishna Marothu, Rajeshwari Rathod
Metabolite identification is a crucial part of the drug discovery process. LC-MS/MS-based metabolite identification has gained widespread use, but the data acquired by the LC-MS/MS instrument is complex, and thus the interpretation of data becomes troublesome. Fortunately, advancements in data mining techniques have simplified the process of data interpretation with improved mass accuracy and provide a potentially selective, sensitive, accurate and comprehensive way for metabolite identification. In this review, we have discussed the targeted (extracted ion chromatogram, mass defect filter, product ion filter, neutral loss filter and isotope pattern filter) and untargeted (control sample comparison, background subtraction and metabolomic approaches) post-acquisition data mining techniques, which facilitate the drug metabolite identification...
August 17, 2017: Bioanalysis
https://www.readbyqxmd.com/read/28815765/new-tools-and-functions-in-data-out-activities-at-protein-data-bank-japan-pdbj
#6
Akira R Kinjo, Gert-Jan Bekker, Hiroshi Wako, Shigeru Endo, Yuko Tsuchiya, Hiromu Sato, Hafumi Nishi, Kengo Kinoshita, Hirofumi Suzuki, Takeshi Kawabata, Masashi Yokochi, Takeshi Iwata, Naohiro Kobayashi, Toshimichi Fujiwara, Genji Kurisu, Haruki Nakamura
The Protein Data Bank Japan (PDBj), a member of the worldwide Protein Data Bank (wwPDB), accepts and processes the deposited data of experimentally determined biological macromolecular structures. In addition to archiving the PDB data in collaboration with the other wwPDB partners, PDBj also provides a wide range of original and unique services and tools, which are continuously improved and updated. Here, we report the new RDB PDBj Mine 2, the WebGL molecular viewer Molmil, the ProMode-Elastic server for normal mode analysis, a virtual reality system for the eF-site protein electrostatic molecular surfaces, the extensions of the Omokage search for molecular shape similarity, and the integration of PDBj and BMRB searches...
August 17, 2017: Protein Science: a Publication of the Protein Society
https://www.readbyqxmd.com/read/28815152/populating-physician-biographical-pages-based-on-emr-data
#7
Feichen Shen, Sunghwan Sohn, Majid Rastegar-Mojarad, Sijia Liu, Joshua J Pankratz, Michael A Hatton, Nancy Sowada, Om K Shrestha, Shawna L Shurson, Hongfang Liu
The physicians' biographical pages are essential in providing information about physicians' specialties. However, physicians may not have biographical pages or the current pages are not comprehensive. We hypothesize that physicians' specialty information can be mined from Electronic Medical Records (EMRs) of their patients. We proposed an automated physician specialty populating (PSP) system that analyzes physician-ascertained diagnoses in EMRs, aggregates them to an appropriate granularity based on the current biographical pages, and populates the biographical pages accordingly...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815138/integrative-network-and-transcriptomics-based-approach-predicts-genotype-specific-drug-combinations-for-melanoma
#8
Kelly E Regan, Philip R O Payne, Fuhai Li
Computational methods for drug combination predictions are needed to identify effective therapies that improve durability and prevent drug resistance in an efficient manner. In this paper, we present SynGeNet, a computational method that integrates transcriptomics data characterizing disease and drug z-score profiles with network mining algorithms in order to predict synergistic drug combinations. We compare SynGeNet to other available transcriptomics-based tools to predict drug combinations validated across melanoma cell lines in three genotype groups: BRAF-mutant, NRAS-mutant and combined...
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
#9
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
#10
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
https://www.readbyqxmd.com/read/28815115/discovering-adverse-drug-events-combining-spontaneous-reports-with-electronic-medical-records-a-case-study-of-conventional-dmards-and-biologics-for-rheumatoid-arthritis
#11
Liwei Wang, Majid Rastegar-Mojarad, Sijia Liu, Huaji Zhang, Hongfang Liu
The use of multiple data sources has been preferred in the surveillance of adverse drug events due to shortcomings of using only a single source. In this study, we proposed a framework where the ADEs associated with interested drugs are systematically discovered from the FDA's Adverse Event Reporting System (AERS), and then validated through mining unstructured clinical notes from Electronic Medical Records (EMRs). This framework has two features. First, a higher priority was given to clinical practice during signal detection and validation...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815113/towards-generation-management-and-exploration-of-combined-radiomics-and-pathomics-datasets-for-cancer-research
#12
Joel Saltz, Jonas Almeida, Yi Gao, Ashish Sharma, Erich Bremer, Tammy DiPrima, Mary Saltz, Jayashree Kalpathy-Cramer, Tahsin Kurc
Cancer is a complex multifactorial disease state and the ability to anticipate and steer treatment results will require information synthesis across multiple scales from the host to the molecular level. Radiomics and Pathomics, where image features are extracted from routine diagnostic Radiology and Pathology studies, are also evolving as valuable diagnostic and prognostic indicators in cancer. This information explosion provides new opportunities for integrated, multi-scale investigation of cancer, but also mandates a need to build systematic and integrated approaches to manage, query and mine combined Radiomics and Pathomics data...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815108/monitoring-biomedical-literature-for-post-market-safety-purposes-by-analyzing-networks-of-text-based-coded-information
#13
Taxiarchis Botsis, Matthew Foster, Kory Kreimeyer, Abhishek Pandey, Richard Forshee
Literature review is critical but time-consuming in the post-market surveillance of medical products. We focused on the safety signal of intussusception after the vaccination of infants with the Rotashield Vaccine in 1999 and retrieved all PubMed abstracts for rotavirus vaccines published after January 1, 1998. We used the Event-based Text-mining of Health Electronic Records system, the MetaMap tool, and the National Center for Biomedical Ontologies Annotator to process the abstracts and generate coded terms stamped with the date of publication...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815103/search-datasets-in-literature-a-case-study-of-gwas
#14
Xiao Dong, Yaoyun Zhang, Hua Xu
One of the missions of the NIH BD2K (Big Data to Knowledge) initiative is to make data discoverable and promote the re-use of existing datasets. Our ultimate goal is to develop a scalable approach that can automatically scan millions of scientific publications and identify underlying data sets. Using Genome-Wide Association Studies (GWAS) as a use case, we conducted an initial study to identify GWAS dataset attributes in MEDLINE abstracts, by developing a hybrid approach that combines domain dictionaries and pattern-based rules...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28813246/the-benefits-of-data-mining
#15
Audrey Bone, Keith Houck
Careful analysis of a database populated by physicians and patients sheds new light on the side effects of drugs.
August 16, 2017: ELife
https://www.readbyqxmd.com/read/28811326/-10m-gift-supports-data-recycling-at-ucsf
#16
(no author information available yet)
The University of California, San Francisco's Institute for Computational Health Sciences has received a $10 million gift to support "data recycling" investigations. The approach to medical research involves mining existing data to potentially uncover new uses for existing drugs and help improve clinical care.
August 15, 2017: Cancer Discovery
https://www.readbyqxmd.com/read/28810903/a-neural-network-multi-task-learning-approach-to-biomedical-named-entity-recognition
#17
Gamal Crichton, Sampo Pyysalo, Billy Chiu, Anna Korhonen
BACKGROUND: Named Entity Recognition (NER) is a key task in biomedical text mining. Accurate NER systems require task-specific, manually-annotated datasets, which are expensive to develop and thus limited in size. Since such datasets contain related but different information, an interesting question is whether it might be possible to use them together to improve NER performance. To investigate this, we develop supervised, multi-task, convolutional neural network models and apply them to a large number of varied existing biomedical named entity datasets...
August 15, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28810710/testing-convergent-evolution-in-auditory-processing-genes-between-echolocating-mammals-and-the-aye-aye-a-percussive-foraging-primate
#18
Richard J Bankoff, Michael Jerjos, Baily Hohman, M Elise Lauterbur, Logan Kistler, George H Perry
Several taxonomically distinct mammalian groups-certain microbats and cetaceans (e.g., dolphins)-share both morphological adaptations related to echolocation behavior and strong signatures of convergent evolution at the amino acid level across seven genes related to auditory processing. Aye-ayes (Daubentonia madagascariensis) are nocturnal lemurs with a specialized auditory processing system. Aye-ayes tap rapidly along the surfaces of trees, listening to reverberations to identify the mines of wood-boring insect larvae; this behavior has been hypothesized to functionally mimic echolocation...
July 1, 2017: Genome Biology and Evolution
https://www.readbyqxmd.com/read/28808275/screening-drug-target-interactions-with-positive-unlabeled-learning
#19
Lihong Peng, Wen Zhu, Bo Liao, Yu Duan, Min Chen, Yi Chen, Jialiang Yang
Identifying drug-target interaction (DTI) candidates is crucial for drug repositioning. However, usually only positive DTIs are deposited in known databases, which challenges computational methods to predict novel DTIs due to the lack of negative samples. To overcome this dilemma, researchers usually randomly select negative samples from unlabeled drug-target pairs, which introduces a lot of false-positives. In this study, a negative sample extraction method named NDTISE is first developed to screen strong negative DTI examples based on positive-unlabeled learning...
August 14, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28808043/allosteric-alterations-in-the-androgen-receptor-and-activity-in-prostate-cancer
#20
REVIEW
Takuma Uo, Stephen R Plymate, Cynthia C Sprenger
Organisms have evolved to generate biological complexity in their proteome and transcriptome from a limited number of genes. This concept holds true for the androgen receptor, which displays a diversity of inclusion/exclusion events in its structural motifs as a mechanism of resistance to the most forefront anti-androgen therapies. More than 20 androgen receptor variants that lack various portions of ligand-binding domain have been identified in human prostate cancer (PCa) samples. Most of the variants are inactive on their own, with a few exceptions displaying constitutive activity...
September 2017: Endocrine-related Cancer
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