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Data Mining Classification Methods Applied In Drug Design

Mária Stachová, Lukáš Sobíšek
2012 Zenodo  
For this purpose logistic regression, Bayesian logistic regression and random forest models were built using R software. TheBayesian logistic regression in Latent GOLD software was created as well.  ...  Those models were applied to predict the biological activity of molecules, potential new drug candidates.  ...  We thank Andrej Boháč for providing us the training set of molecules and we also thank Marek Skoršepa for scoring our selected molecules.  ... 
doi:10.5281/zenodo.1329401 fatcat:fyhlrybebbddpd3jy6rlq5rozm

A Bayesian network approach to assess and predict software quality using activity-based quality models

Stefan Wagner
2009 Proceedings of the 5th International Conference on Predictor Models in Software Engineering - PROMISE '09  
This paper describes how activity-based quality models can be used to derive BN models for quality assessment and pre- diction.  ...  However, these models lack an operationalisation that allows to use them in assessment and prediction of quality.  ...  Bayesian networks and the corresponding tool support make it easy to build models and get quantitative results.  ... 
doi:10.1145/1540438.1540447 dblp:conf/promise/Wagner09 fatcat:db37rscptzgrll7miv3d2vb5iq

A Bayesian network approach to assess and predict software quality using activity-based quality models

Stefan Wagner
2010 Information and Software Technology  
Objective: The qualitative knowledge contained in activity-based quality models are an abundant basis for building Bayesian networks for quality assessment.  ...  However, these models lack an operationalisation that would allow them to be used in assessment and prediction of quality.  ...  Bayesian networks and the corresponding tool support make it easy to build models and get quantitative results.  ... 
doi:10.1016/j.infsof.2010.03.016 fatcat:guc3zfwggjhhxg3bxjk7ylylo4

Features of SAS Enterprise Guide for probabilistic Modeling System, Macroeconomic Analysis and Forecasting

Prosyankina-Zharova Tetyana, Terentiev Oleksandr, Bidyuk Petro, Makukha Mikhailo
2016 Journal of Mathematics and System Science  
This paper addresses to the problem of using SAS Enterprise Guide 6.1 as a means for building probabilistic models and as optimum method of modeling gross domestic product in terms of the economic crisis  ...  SFPP G4877 "Modeling and Mitigation of Social Disasters Caused by Catastrophes and Terrorism" the problems of scientific prediction of national economy for the period to 2030 as one of the measures preventing  ...  model as a Bayesian network using multiple regression.  ... 
doi:10.17265/2159-5291/2016.03.003 fatcat:qhuc2litzvacfk47z54ax3r4di

Customer churn predictive modeling by classification methods

Oleksandr Dorokhov, Kuznets Kharkiv National University of Economics, Ukraine,, Liudmyla Dorokhova, Lyudmyla Malyarets, Iryna Ushakova, National University of Pharmacy, Ukraine, Kuznets Kharkiv National University of Economics, Ukraine,, Kuznets Kharkiv National University of Economics, Ukraine,
SPSS Modeler was used as a tool for building models. 2000 Mathematics Subject Classification: 90B50, 91B50, 62C12, 62C10  ...  The Bayesian model is constructed for a Naive and Markov structure. Customer service has become a key factor in the customer churn in all three models.  ...  The decision tree model provides additional benefits.  ... 
doi:10.31926/but.mif.2020. fatcat:xl3vu47qz5dxpnczgzy6vqyidq

Applying Machine Learning Techniques to Analysis of Gene Expression Data: Cancer Diagnosis [chapter]

Kyu-Baek Hwang, Dong-Yeon Cho, Sang-Wook Park, Sung-Dong Kim, Byoung-Tak Zhang
2002 Methods of Microarray Data Analysis  
Machine learning techniques, such as Bayesian networks, neural trees, and radial basis function (RBF) networks, are used for the analysis of the CAMDA Data Set 2.  ...  These techniques have their own properties including the ability of finding important genes for cancer classification, revealing relationships among genes, and classifying cancer.  ...  In general, the unrestricted multinomial distribution model and the linear regression model are used for the local probability distribution of Bayesian networks.  ... 
doi:10.1007/978-1-4615-0873-1_13 fatcat:ftaxuah6qnfnvlzzpmj6nz75q4

A Comparative Analysis of the Ensemble Methods for Drug Design [article]

Rifkat Davronova, Fatima Adilovab
2020 arXiv   pre-print
Quantitative structure-activity relationship (QSAR) is a computer modeling technique for identifying relationships between the structural properties of chemical compounds and biological activity.  ...  Thus, a technique for complex ensemble method is proposed that builds diversified models and integrates them.  ...  The authors are is also thankful to several colleagues in both laboratories, who were engaged in many scientific discussions that helped the authors formulate the best current practices modeling discussed  ... 
arXiv:2012.07640v1 fatcat:p4scqkd5wrgurb7hbmjlyqrkh4

Patent Analysis Using Bayesian Data Analysis and Network Modeling

Sangsung Park, Sunghae Jun
2022 Applied Sciences  
Next, using Bayesian additive regression trees, we analyzed the structured patent data to construct technology scenarios for drones.  ...  We searched the patent documents related to drone technology and transformed them to structured data using text mining techniques.  ...  (Step 4) Performing Bayesian Additive Regression Trees (BART) model (4-1) Comparing p-values of explanatory keywords using a multiple regression model. (4-2) Selecting important keywords using BART modeling  ... 
doi:10.3390/app12031423 fatcat:iqoqgy4y6vgcfdjp4sklrr64su

Machine Learning in Catalysis, From Proposal to Practicing

Wenhong Yang, Timothy Tizhe Fidelis, Wen-Hua Sun
2019 ACS Omega  
This in turn will accurately extract the underlying mechanism in the model that converts readily available data and precatalysts into their promising and useful ones.  ...  Recently, machine learning (ML) methods have gained popularity and have performed as powerfully predictive tools in various areas of academic and industrious activities.  ...  There have been a small number of reports of quantitative structureactivity/properties relationship (QSA/PR) studies of olefin polymerization using metallocene catalysts by Cruz and co-workers.  ... 
doi:10.1021/acsomega.9b03673 pmid:31956754 pmcid:PMC6963892 fatcat:zd2fui4e3ja5vasx7debt4kpyi

Inferring cellular networks – a review

Florian Markowetz, Rainer Spang
2007 BMC Bioinformatics  
The first part of the review deals with conditional independence models including Gaussian graphical models and Bayesian networks.  ...  Although this area of research is vast and fast developing, we show that most currently used methods can be organized by a few key concepts.  ...  [20, 26] , classification trees [25, 27] , or sparse Bayesian regression [19, 28] .  ... 
doi:10.1186/1471-2105-8-s6-s5 pmid:17903286 pmcid:PMC1995541 fatcat:3cqptcs6ord5zkrhnyuvhu7svq

A Bayesian regression tree approach to identify the effect of nanoparticles' properties on toxicity profiles

Cecile Low-Kam, Donatello Telesca, Zhaoxia Ji, Haiyuan Zhang, Tian Xia, Jeffrey I. Zink, Andre E. Nel
2015 Annals of Applied Statistics  
We introduce a Bayesian multiple regression tree model to characterize relationships between physico-chemical properties of nanoparticles and their in-vitro toxicity over multiple doses and times of exposure  ...  The proposed technique integrates Bayesian trees for modeling threshold effects and interactions, and penalized B-splines for dose- and time-response surface smoothing.  ...  The nano-informatics literature reports several Quantitative Structure-Activity Relationship (QSAR) models.  ... 
doi:10.1214/14-aoas797 fatcat:e7vlwsggf5detndtafgmbqm35y


Bruce G Marcot
2006 Northwestern Naturalist  
I suggest the use of influence diagrams in structuring causal webs and structural equation modeling to quantify relations, as a general framework for building models of habitat from which a known degree  ...  Habitat models address only 1 component of biodiversity but can be useful in addressing and managing single or multiple species and ecosystem functions, for projecting disturbance regimes, and in supporting  ...  Next, the influence diagrams can be used as the basis for quantitatively modeling variable relations, as with Bayesian belief networks and information-theoretic approaches.  ... 
doi:10.1898/1051-1733(2006)87[56:hmfbc];2 fatcat:53kqbckswna7phdr6mdu555zf4

High Expression of Caspase-8 Associated with Improved Survival in Diffuse Large B-Cell Lymphoma: Machine Learning and Artificial Neural Networks Analyses

Joaquim Carreras, Yara Yukie Kikuti, Giovanna Roncador, Masashi Miyaoka, Shinichiro Hiraiwa, Sakura Tomita, Haruka Ikoma, Yusuke Kondo, Atsushi Ito, Sawako Shiraiwa, Kiyoshi Ando, Naoya Nakamura (+1 others)
2021 BioMedInformatics  
Next, the Caspase-8 protein expression was modeled using predictive analytics, and a high overall predictive accuracy (>80%) was obtained with CHAID decision tree, Bayesian network, discriminant analysis  ...  , C5 tree, logistic regression, and Artificial Intelligence Neural Network methods (both Multilayer perceptron and Radial basis function); the most relevant markers were cCASP3, E2F1, TP53, cPARP, MDM2  ...  Twelve different models were executed, including the algorithms of C5.0 node that builds a decision tree or a rule set, logistic regression, Bayesian Network, discriminant analysis, k-Nearest Neighbor  ... 
doi:10.3390/biomedinformatics1010003 fatcat:ja7bnfgakraivntfnaacgkzufi

A distributed architecture for phishing detection using Bayesian Additive Regression Trees

Saeed Abu-Nimeh, Dario Nappa, Xinlei Wang, Suku Nair
2008 2008 eCrime Researchers Summit  
The present study proposes a distributed architecture hinging on machine learning approaches to detect phishing emails in a mobile environment based on a modified version of Bayesian Additive Regression  ...  Trees (BART).  ...  Rather than using a single regression tree, BART uses a sum-of-trees model that can account for additive effects.  ... 
doi:10.1109/ecrime.2008.4696965 dblp:conf/ecrime/Abu-NimehNWN08 fatcat:wqlnh3yivjaircdzzdeomg2i44

Tersine Lojistik Sürecinde İade Oranlarının Tahmini İçin Makine Öğrenme Algoritmalarının Kullanılması

Ayşe Nur Adıgüzel Tüylü, Ergün Eroğlu
2019 Alphanumeric Journal  
In order to reduce resource usage and cost at first step, in addition to producing the correct quantity, these products must be sent to branches, in correct properties (amount, color, size, model...) and  ...  Statistical methods, artificial intelligence and machine learning methods are used because of the difficulty of establishing mathematical models in multi-parameter and multi-variable problems.  ...  A decision tree structure consists of root, inner and leaf nodes. The tree structure is used to classify unknown data records. Tree leaves consist of class labels where data items are grouped.  ... 
doi:10.17093/alphanumeric.541307 fatcat:czded3o6sfadhok2pbbdyicbde
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