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ATHENA: Identifying interactions between different levels of genomic data associated with cancer clinical outcomes using grammatical evolution neural network

Dokyoon Kim, Ruowang Li, Scott M Dudek, Marylyn D Ritchie
2013 BioData Mining  
Results: Here, we proposed an integrative framework for identifying interactions within/ between multi-levels of genomic data associated with cancer clinical outcomes using the Grammatical Evolution Neural  ...  interactions between them associated with clinical outcomes.  ...  In addition, we gratefully acknowledge the TCGA Consortium and all its members for the TCGA Project initiative, for providing sample, tissues, data processing and making data and results available.  ... 
doi:10.1186/1756-0381-6-23 pmid:24359638 pmcid:PMC3912499 fatcat:dhqhbfmkuffbnedewmqwcscf2q

Initialization parameter sweep in ATHENA

Emily Rose Holzinger, Carrie C. Buchanan, Scott M. Dudek, Eric C. Torstenson, Stephen D. Turner, Marylyn D. Ritchie
2010 Proceedings of the 12th annual conference on Genetic and evolutionary computation - GECCO '10  
The Analysis Tool for Heritable and Environmental Network Associations (ATHENA) is an analytical tool that incorporates grammatical evolution neural networks (GENN) to detect interactions among genetic  ...  This research addresses how different parameter settings affect detection of disease models involving interactions.  ...  Acknowledgments This project was funded by NIH grants LM010040, NS066638-01, HG004608, HL065962, 5T32GM080178 and the Public Health Service award T32 GM07347 from the National Institute of General Medical  ... 
doi:10.1145/1830483.1830519 pmid:21152364 pmcid:PMC2997651 dblp:conf/gecco/HolzingerBDTTR10 fatcat:nzrpguqm75bqfoobtw4pno42vm

ATHENA: a tool for meta-dimensional analysis applied to genotypes and gene expression data to predict HDL cholesterol levels

Emily R Holzinger, Scott M Dudek, Alex T Frase, Ronald M Krauss, Marisa W Medina, Marylyn D Ritchie
2013 Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing  
For this study we used the Analysis Tool for Heritable and Environmental Network Associations (ATHENA) to integrate high-throughput SNPs and gene expression variables (EVs) to predict high-density lipoprotein  ...  A popular analytical method thus far has been the genome-wide association study (GWAS), which assesses the association of single nucleotide polymorphisms (SNPs) with the trait of interest.  ...  ATHENA modeling: Grammatical Evolution Neural Networks-GENN uses a variation of genetic programming (GP) called grammatical evolution (GE) to optimize artificial neural networks to identify a model that  ... 
pmid:23424143 pmcid:PMC3587764 fatcat:dv3yrw7dwfhhdmoszukobb7unq

ATHENA: A TOOL FOR META-DIMENSIONAL ANALYSIS APPLIED TO GENOTYPES AND GENE EXPRESSION DATA TO PREDICT HDL CHOLESTEROL LEVELS

EMILY R. HOLZINGER, SCOTT M. DUDEK, ALEX T. FRASE, RONALD M. KRAUSS, MARISA W. MEDINA, MARYLYN D. RITCHIE
2012 Biocomputing 2013  
For this study we used the Analysis Tool for Heritable and Environmental Network Associations (ATHENA) to integrate high-throughput SNPs and gene expression variables (EVs) to predict high-density † Work  ...  A popular analytical method thus far has been the genome-wide association study (GWAS), which assesses the association of single nucleotide polymorphisms (SNPs) with the trait of interest.  ...  ATHENA modeling: Grammatical Evolution Neural Networks GENN uses a variation of genetic programming (GP) called grammatical evolution (GE) to optimize artificial neural networks to identify a model that  ... 
doi:10.1142/9789814447973_0038 fatcat:vcjn6jdfrfa6vjtetlsvcf7g2y

Knowledge-driven genomic interactions: an application in ovarian cancer

Dokyoon Kim, Ruowang Li, Scott M Dudek, Alex T Frase, Sarah A Pendergrass, Marylyn D Ritchie
2014 BioData Mining  
Methods: Thus, we propose a novel approach for identifying knowledge-driven genomic interactions and applying it to discover models associated with cancer clinical phenotypes using grammatical evolution  ...  Results: We identified knowledge-driven genomic interactions associated with cancer stage from single knowledge bases such as sources of pathway-pathway interaction, but also knowledge-driven genomic interactions  ...  This work is also supported by a grant with the Pennsylvania Department of Health using Tobacco CURE Funds.  ... 
doi:10.1186/1756-0381-7-20 pmid:25214892 pmcid:PMC4161273 fatcat:mx32nzzcnjdfpe3fuz3rpbb764

Predicting censored survival data based on the interactions between meta-dimensional omics data in breast cancer

Dokyoon Kim, Ruowang Li, Scott M. Dudek, Marylyn D. Ritchie
2015 Journal of Biomedical Informatics  
In order to predict censored survival time, martingale residuals were calculated as a new continuous outcome and a new fitness function used by the grammatical evolution neural network (GENN) based on  ...  interactions within/between meta-dimensional genomic features associated with survival.  ...  The results published here are in whole or part based upon data generated by The Cancer Genome Atlas pilot project established by the NCI and NHGRI.  ... 
doi:10.1016/j.jbi.2015.05.019 pmid:26048077 pmcid:PMC4550096 fatcat:7i7lejvfmvfr7ha4r7noyfcicq

Using knowledge-driven genomic interactions for multi-omics data analysis: metadimensional models for predicting clinical outcomes in ovarian carcinoma

Dokyoon Kim, Ruowang Li, Anastasia Lucas, Shefali S Verma, Scott M Dudek, Marylyn D Ritchie
2016 JAMIA Journal of the American Medical Informatics Association  
To overcome this variability, we previously developed a new approach incorporating prior biological knowledge that identifies knowledge-driven genomic interactions associated with outcomes of interest.  ...  We found that each knowledge-driven genomic interaction model, based on different genomic datasets, contains different sets of pathway features, which suggests that each genomic data type may contribute  ...  The results published here are in whole or part based upon data generated by The Cancer Genome Atlas pilot project established by the National Cancer Institute and the National Human Genome Research Institute  ... 
doi:10.1093/jamia/ocw165 pmid:28040685 pmcid:PMC5391734 fatcat:5menlwf4irbc3i2dpxfusbmxyq

Binning somatic mutations based on biological knowledge for predicting survival: an application in renal cell carcinoma

Dokyoon Kim, Ruowang Li, Scott M Dudek, John R Wallace, Marylyn D Ritchie
2015 Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing  
Driver mutations show strong associations with cancer clinical outcomes such as survival.  ...  Enormous efforts of whole exome and genome sequencing from hundreds to thousands of patients have provided the landscape of somatic genomic alterations in many cancer types to distinguish between driver  ...  This work is also supported by a grant with the Pennsylvania Department of Health using Tobacco CURE Funds.  ... 
pmid:25592572 pmcid:PMC4299944 fatcat:ljzcvd7xuvavdhalew6jk4xwea

More Is Better: Recent Progress in Multi-Omics Data Integration Methods

Sijia Huang, Kumardeep Chaudhary, Lana X. Garmire
2017 Frontiers in Genetics  
To improve the clinical outcome prediction, a gamut of software tools has been developed.  ...  Considerable work has been done with the advent of high-throughput studies, which have enabled the data access for downstream analyses.  ...  Based on neural networks, grammatical evolution algorithm is utilized to train the model with selected features that are less noisy and significantly associated with clinical outcomes.  ... 
doi:10.3389/fgene.2017.00084 pmid:28670325 pmcid:PMC5472696 fatcat:ccdbkwpqufbqjitaxs2kkxcs4y

A Review for Detecting Gene-Gene Interactions Using Machine Learning Methods in Genetic Epidemiology

Ching Lee Koo, Mei Jing Liew, Mohd Saberi Mohamad, Abdul Hakim Mohamed Salleh
2013 BioMed Research International  
Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs), support vector machine (SVM), and random forests (RFs)  ...  Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect  ...  Grammatical evolution neural network (GENN) was introduced to detecting gene-gene or gene-environment interactions in high dimensional genetic epidemiological data [16] .  ... 
doi:10.1155/2013/432375 pmid:24228248 pmcid:PMC3818807 fatcat:5exezft7q5a47iibtf2cowljsm

A multi-omics data simulator for complex disease studies and its application to evaluate multi-omics data analysis methods for disease classification

Ren-Hua Chung, Chen-Yu Kang
2019 GigaScience  
An integrative multi-omics analysis approach that combines multiple types of omics data including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and microbiomics has become increasing  ...  Although many multi-omics analysis methods have been developed for complex disease studies, only a few simulation tools that simulate multiple types of omics data and model their relationships with disease  ...  Finally, ATHENA uses grammatical evolution neural networks (GENNs), which optimize artificial neural networks based on genetic programming, to construct a meta-dimensional model from multiomics data for  ... 
doi:10.1093/gigascience/giz045 pmid:31029063 pmcid:PMC6486474 fatcat:53y7ygmdfjakdk5pj7wspc2nwe

Transcriptomics in Toxicogenomics, Part III: Data Modelling for Risk Assessment

Angela Serra, Michele Fratello, Luca Cattelani, Irene Liampa, Georgia Melagraki, Pekka Kohonen, Penny Nymark, Antonio Federico, Pia Anneli Sofia Kinaret, Karolina Jagiello, My Kieu Ha, Jang-Sik Choi (+8 others)
2020 Nanomaterials  
Indeed, the publicly available omics datasets are constantly increasing together with a plethora of different methods that are made available to facilitate their analysis, interpretation and the generation  ...  After careful planning of exposure conditions and data preprocessing, the TGx data can be used in predictive toxicology, where more advanced modelling techniques are applied.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/nano10040708 pmid:32276469 pmcid:PMC7221955 fatcat:7n4mf747jjhpjhkvsxqwbu2kfq

Computational Methods for Single-Cell Imaging and Omics Data Integration

Ebony Rose Watson, Atefeh Taherian Fard, Jessica Cara Mar
2022 Frontiers in Molecular Biosciences  
These imaging technologies complement omics-based data in biomedical research because they are helpful for identifying associations between genotype and phenotype, along with functional changes occurring  ...  Although the use of imaging data is well established in biomedical research, its primary application has been to observe phenotypes at the tissue or organ level, often using medical imaging techniques  ...  ., 2013) used grammatical evolution neural network (GENN) to predict clinical outcomes for cancer patients by integrating gene copy number, DNA methylation, miRNA and gene expression data.  ... 
doi:10.3389/fmolb.2021.768106 pmid:35111809 pmcid:PMC8801747 fatcat:zrqpododa5gyxoti5fnx3llepq

Cigarette-Derived Nicotine is not a Medicine

Andrew C Parrott
2003 World Journal of Biological Psychiatry  
Acknowledgement The authors would like to thank the Tourette Syndrome (UK) Association for their support and encouragement. Acknowledgements  ...  Data were compared with previous data from similar clinic samples.  ...  Both of these sets of data were collected from the same clinic, the only difference being a seven-year time lapse.  ... 
doi:10.3109/15622970309167951 pmid:12692774 fatcat:qvb6bz72vneylpdnhaes6ziqfm

Natural Language Processing and Information Extraction

Νικόλαος Ε. Στυλιανού
2021
to identify.  ...  The incrementally proposed changes to the Deep Neural Network architectures intend to improve the performance in all biomedical entity categories and provide more efficient solutions.  ...  Dermatologist-level classification of skin cancer with deep neural networks. nature, 542(7639):115–118. Mina Farid. 2020. Extracting and Cleaning RDF Data. University of Waterloo.  ... 
doi:10.26262/heal.auth.ir.334427 fatcat:xnmddj3t7jg7poadfwrsxqsi6a
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