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BioNav: An Ontology-Based Framework to Discover Semantic Links in the Cloud of Linked Data [chapter]

María-Esther Vidal, Louiqa Raschid, Natalia Márquez, Jean Carlo Rivera, Edna Ruckhaus
2010 Lecture Notes in Computer Science  
We demonstrate BioNav, a system to efficiently discover potential novel associations between drugs and diseases by implementing Literature-Based Discovery techniques.  ...  We discuss the formalization of a discovery request as a link-analysis and authority-based problem, and show that the top ranked target objects are in correspondence with the potential novel discoveries  ...  BioNav uses link-analysis and authority-flow ranking metrics to rank the discovered associations.  ... 
doi:10.1007/978-3-642-13489-0_40 fatcat:rl7fu5y2grbhvh6le3ta6fixiy

DISCOVERY OF MOLECULARLY TARGETED THERAPIES

Kelly Regan, Zachary Abrams, Michael Sharpnack, Arunima Srivastava, Kun Huang, Nigam Shah, Philip R O Payne
2016 Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing  
optimize large-scale regression-based association studies (Verma et al) and to discover dependencies between genes differ across disease conditions (Speyer et al).  ...  This work seeks to address the problem of discovering associations between single nucleotide polymorphisms (SNPs) and phenotypes on a large scale.  ... 
pmid:26776168 pmcid:PMC4874173 fatcat:ccbs2avjdja3lahhjnaifrqgjq

DISCOVERY OF MOLECULARLY TARGETED THERAPIES

KELLY REGAN, ZACHARY ABRAMS, MICHAEL SHARPNACK, ARUNIMA SRIVASTAVA, KUN HUANG, NIGAM SHAH, PHILIP R.O. PAYNE
2015 Biocomputing 2016  
At a high level, the exemplary efforts made by authors contributing to this session of PSB 2016 provide a broad cross-section of such novel methods, and focus on: large-scale regression-based association  ...  This work seeks to address the problem of discovering associations between single nucleotide polymorphisms (SNPs) and phenotypes on a large scale.  ... 
doi:10.1142/9789814749411_0001 fatcat:5zfvhqmbhzb6zcqyo3zezsoyeu

Genome-wide discovery of hidden genes mediating known drug-disease association using KDDANet

Hua Yu, Lu Lu, Ming Chen, Chen Li, Jin Zhang
2021 npj Genomic Medicine  
Importantly, KDDANet can be used to discover the shared genes mediating multiple KDDAs.  ...  AbstractMany of genes mediating Known Drug-Disease Association (KDDA) are escaped from experimental detection.  ...  To identify novel drug combinations, Zhao et al. integrated the molecular and pharmacological data and developed a novel computational approach 17 .  ... 
doi:10.1038/s41525-021-00216-6 pmid:34131148 fatcat:owsbn7ea6ze6zd44jlhrff64nq

Multilevel text mining for bone biology

Omkar Tilak, Andrew Hoblitzell, Snehasis Mukhopadhyay, Qian You, Shiaofen Fang, Yuni Xia, Joseph Bidwell
2011 Concurrency and Computation  
The novel relationships between biological pathways thus discovered constitute new hypotheses which can be verified using experiments.  ...  Novel relationships between domains are extracted by the transitive text mining analysis. In the second level, these newly discovered relationships are used to extract relevant protein names.  ...  To filter the most significant findings, a ranking system is devised to rate our predicted novel genes.  ... 
doi:10.1002/cpe.1788 fatcat:ds2nloracfbx7mdlyurjunbx7a

A genomics-based systems approach towards drug repositioning for rheumatoid arthritis

Rong Xu, QuanQiu Wang
2016 BMC Genomics  
When compared to a study that used GWAS data to directly connect RA-associated genes to drug targets ("direct genetics-based" approach), our algorithm ("indirect genetics-based") achieved a comparable  ...  We developed a network-based ranking algorithm to prioritize diseases genetically-related to RA (RA-related diseases).  ...  While previous studies demonstrated that directly linking disease-associated genes from GWAS data to drug targets can lead to novel drug discovery, our study provides an alternative strategy to capitalize  ... 
doi:10.1186/s12864-016-2910-0 pmid:27557330 pmcid:PMC5001200 fatcat:qvxqsft2yrhohfdkzjx3qn5ij4

Inferring Gene-Phenotype Associations via Global Protein Complex Network Propagation

Peng Yang, Xiaoli Li, Min Wu, Chee-Keong Kwoh, See-Kiong Ng, Thomas Mailund
2011 PLoS ONE  
We tested RWPCN on predicting gene-phenotype associations using leave-oneout cross-validation; our method was observed to outperform existing approaches.  ...  disease genes better than traditional approaches that used only protein-phenotype associations.  ...  Acknowledgments We would like to thank the authors of the RWRH and CIPHER algorithms for sharing the source codes of their systems. Author Contributions  ... 
doi:10.1371/journal.pone.0021502 pmid:21799737 pmcid:PMC3143124 fatcat:das6g7alozdmhotry74gguwmym

Text mining for bone biology

Andrew Hoblitzell, Snehasis Mukhopadhyay, Qian You, Shiaofen Fang, Yuni Xia, Joseph Bidwell
2010 Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing - HPDC '10  
flow.  ...  Extraction and visualization of relationships between biological entities appearing in these databases offers the opportunity of keeping researchers up-to-date in their research domain.  ...  A Thesaurus-based text analysis approach is used to discover the existence of relationships.  ... 
doi:10.1145/1851476.1851552 dblp:conf/hpdc/HoblitzellMYFXB10 fatcat:xmgm2nmdavh4ziop2ylvh27vuq

Network biology methods integrating biological data for translational science

G. Bebek, M. Koyuturk, N. D. Price, M. R. Chance
2012 Briefings in Bioinformatics  
Currently, much data exist in silos and is not analyzed in frameworks where all data are brought to bear in the development of biomarkers and novel functional targets. This is beginning to change.  ...  Network biology approaches, which emphasize the interactions between genes, proteins and metabolites provide a framework for data integration such that genome, proteome, metabolome and other -omics data  ...  Acknowledgements The authors would like to acknowledge James Eddy for making  ... 
doi:10.1093/bib/bbr075 pmid:22390873 pmcid:PMC3404396 fatcat:cdfuoph3o5b5bcpdkfgop4fzpy

Using Literature Based Discovery to Gain Insights Into the Metabolomic Processes of Cardiac Arrest

Sam Henry, D. Shanaka Wijesinghe, Aidan Myers, Bridget T. McInnes
2021 Frontiers in Research Metrics and Analytics  
We used LBD to help discover diseases implicitly linked via these metabolites of interest. Results of LBD indicated a strong link between Fish Eye disease and cardiac arrest.  ...  In this paper, we describe how we applied LBD techniques to discover lecithin cholesterol acyltransferase (LCAT) as a druggable target for cardiac arrest.  ...  This LBD approach allows for a computational approach to verify data collection and analysis, rather than an arbitrary approach.  ... 
doi:10.3389/frma.2021.644728 pmid:34250435 pmcid:PMC8267364 fatcat:5y6v6e7afrcxxmvrgnmt4wtzem

Large-Scale Discovery of Disease-Disease and Disease-Gene Associations

Djordje Gligorijevic, Jelena Stojanovic, Nemanja Djuric, Vladan Radosavljevic, Mihajlo Grbovic, Rob J. Kulathinal, Zoran Obradovic
2016 Scientific Reports  
In this paper, EHR data is used to discover novel relationships between diseases by studying their comorbidities (co-occurrences in patients).  ...  In addition, the use of the proposed methodology is extended to discover novel disease-gene associations by including valuable domain knowledge from genome-wide association studies.  ...  Acknowledgements The authors gratefully acknowledge the support of Defense  ... 
doi:10.1038/srep32404 pmid:27578529 pmcid:PMC5006166 fatcat:dhps6defvbg6hpbayjdh5swp4i

Discovery of Critical Nodes in Road Networks Through Mining From Vehicle Trajectories

Ming Xu, Jianping Wu, Mengqi Liu, Yunpeng Xiao, Haohan Wang, Dongmei Hu
2018 IEEE transactions on intelligent transportation systems (Print)  
In this paper, we propose a novel data-driven based approach named CRRank to rank important crossroads.  ...  To compute the importance scores of crossroads accurately, we propose a HITS-like ranking algorithm, in which a procedure of score propagation on our tripartite graph is performed.  ...  In this paper, we aim to discover the important nodes in the road network using a novel data-driven framework named CRRank.  ... 
doi:10.1109/tits.2018.2817282 fatcat:fecmwulo7vfbpkivxciwct2ymy

Challenges in personalized authority flow based ranking of social media

Hassan Sayyadi, John Edmonds, Vagelis Hristidis, Louiqa Raschid
2010 Proceedings of the 19th ACM international conference on Information and knowledge management - CIKM '10  
We then apply personalized authority flow based ranking algorithms based on the random surfer model.  ...  In this research, we extend a social media dataset to exploit the associations between authors, blog posts, and categories (topics) of the posts.  ...  CONCLUSIONS We extended a social media dataset and provided accurate personalized authority flow based ranking for various type of virtual users.  ... 
doi:10.1145/1871437.1871634 dblp:conf/cikm/SayyadiEHR10 fatcat:tlazx4sr2vbsxmicl44iu43kha

Integrative Networks Illuminate Biological Factors Underlying Gene–Disease Associations

Arjun Krishnan, Jaclyn N. Taroni, Casey S. Greene
2016 Current Genetic Medicine Reports  
Once constructed, these networks provide the means to identify broad biological patterns underlying genes associated with complex traits and diseases.  ...  ABSTRACT Integrative networks combine multiple layers of biological data into a model of how genes work together to carry out cellular processes.  ...  They used this approach in conjunction with the brain-specific network, developed previously [8] , to discover novel candidate genes associated with autism spectrum disorder (ASD).  ... 
doi:10.1007/s40142-016-0102-5 fatcat:kidqk7ei7bfzxfszk7nmdpo4xi

Integrative networks illuminate biological factors underlying gene-disease associations [article]

Arjun Krishnan, Jaclyn N Taroni, Casey S Greene
2016 bioRxiv   pre-print
Once constructed, these networks provide the means to identify broad biological patterns underlying genes associated with complex traits and diseases.  ...  Integrative networks combine multiple layers of biological data into a model of how genes work together to carry out cellular processes.  ...  They used this approach in conjunction with the brain-specific network, developed previously [8] , to discover novel candidate genes associated with autism spectrum disorder (ASD).  ... 
doi:10.1101/062695 fatcat:pqccv76v4zgwlfstlpwcuqqjlu
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