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Ensemble transcript interaction networks: A case study on Alzheimer's disease

Rubén Armañanzas, Pedro Larrañaga, Concha Bielza
2012 Computer Methods and Programs in Biomedicine  
Second, we use the ensemble approach Alzheimer's disease to study four types of samples: EC and dentate gyrus (DG) samples from both patients and High-throughput data controls.  ...  The analysis is conducted from two Bayesian network classifiers perspectives.  ...  R.A. is supported by a Juan de la Cierva postdoctoral fellowship (MICINN).  ... 
doi:10.1016/j.cmpb.2011.11.011 pmid:22281045 fatcat:nstoajzwfnbdzcdkv3owogrifu

Active learning of causal Bayesian networks using ontologies: A case study

Montassar Ben Messaoud, Philippe Leray, Nahla Ben Amor
2013 The 2013 International Joint Conference on Neural Networks (IJCNN)  
Due to its high impact in various applications involving reasoning tasks, machine learning researchers have proposed a number of techniques to learn Causal Bayesian Networks.  ...  In this paper, we spread our previous works which foster greater collaboration between causal discovery and ontology evolution so as to evaluate them on real case study.  ...  Causal Bayesian Networks A Causal Bayesian network (CBN), also known as a Markovian model, is represented by a tuple (G,P), where: (i) G is a DAG, called a causal graph, over a set X={X 1 , X 2 ,.., X  ... 
doi:10.1109/ijcnn.2013.6706815 dblp:conf/ijcnn/MessaoudLA13 fatcat:ih2ji77ijrch7fz577m6tmix2q

Feature extraction using Latent Dirichlet Allocation and Neural Networks: A case study on movie synopses [article]

Despoina Christou
2016 arXiv   pre-print
Although Neural Networks for distributed paragraph representations are considered the state of the art for extracting paragraph vectors, we show that a quick topic analysis model such as Latent Dirichlet  ...  This dissertation employs Neural Networks for distributed paragraph representations, and Latent Dirichlet Allocation to capture higher level features of paragraph vectors.  ...  Pitts [34] are inspired by biological neural networks and they are used to estimate or approximate functions given large data as input, generally unknown.  ... 
arXiv:1604.01272v1 fatcat:tcmbvywmazc5bnjj3h73msszha

Repositioning drugs by targeting network modules: a Parkinson's disease case study

Zongliang Yue, Itika Arora, Eric Y. Zhang, Vincent Laufer, S. Louis Bridges, Jake Y. Chen
2017 BMC Bioinformatics  
Using weighted gene correlation network analysis (WGCNA) software package in R, we conducted enrichment analysis of data from a GWAS of PD.  ...  to counteract loss or perturbation of a single member of the network.  ...  Availability of data and materials PAGER database is available online http://discovery.informatics.uab.edu/PAGER. DMAP database is available online http://discovery.informatics.uab.edu/cmaps.  ... 
doi:10.1186/s12859-017-1889-0 pmid:29297292 pmcid:PMC5751600 fatcat:377yldknwvfmre6dtradaytbra

Data Mining of Students' Performance: Turkish Students as a Case Study

Oyebade K. Oyedotun, Sam Nii Tackie, Ebenezer O. Olaniyi, Adnan Khashman
2015 International Journal of Intelligent Systems and Applications  
To validate the power of neural networks in data mining, Turkish students' performance database has been used; feedforward and radial basis function networks were trained for this task.  ...  This research exploits neural networks as a data mining tool in predicting the number of times a student repeats a course, considering some attributes relating to the course itself, the teacher, and the  ...  Input Data The data that were used in this work to validate the power of neural networks in data mining and the prediction of how many times a student will repeat a course has 30 attributes, which are  ... 
doi:10.5815/ijisa.2015.09.03 fatcat:l4st2jaunrhelgjtct6aetp75a

Data Mining and Knowledge Extraction in the Risk Based Insurance Audit: A Case Study (City of Tehran)

Hossein Amirinia, MA Afshar Kazemi, Zahra Alipoor Darvish
2015 IJARCCE  
Nowadays, data mining techniques are widely used in various industries.  ...  The data was then divided into the two categories of Training Set and Test Set and given to the following four algorithms: Neural Network, Decision Tree, Bayesian and Support Vector Machine.  ...  A. Neural Network Neural network is a method that imitates human brain using a set of interconnected nodes. This method is based on computer models of biological neurons.  ... 
doi:10.17148/ijarcce.2015.4892 fatcat:o3jvjym7p5fufottkqc5ahke3e

Topic Space Trajectories: A case study on machine learning literature [article]

Bastian Schäfermeier and Gerd Stumme and Tom Hanika
2020 arXiv   pre-print
We show the applicability of our approach on a publication corpus spanning 50 years of machine learning research from 32 publication venues.  ...  As an attempt to support human analysts, we present topic space trajectories, a structure that allows for the comprehensible tracking of research topics.  ...  The topic on the y-axis is more concerned with the biologic motivation of neural networks and with dynamic neural networks (i.e., recurrent and spiking neural networks).  ... 
arXiv:2010.12294v2 fatcat:hxsstz72vjelxhz5a64zk24xe4

Predicting PM2.5Concentrations Using Artificial Neural Networks and Markov Chain, a Case Study Karaj City

Gholamreza Asadollahfardi, Hossein Zangooei, Shiva Homayoun Aria
2016 Asian Journal of Atmospheric Environment  
In this study, the concentration of PM 2.5 was predicted by applying a multilayer percepteron (MLP) neural network, a radial basis function (RBF) neural network and a Markov chain model.  ...  Two months of hourly data including temperature, NO, NO 2 , NO x , CO, SO 2 and PM 10 were used as inputs to the artifi cial neural networks.  ...  Fig. 2 indicates the MLP neural network used in this study.  ... 
doi:10.5572/ajae.2016.10.2.067 fatcat:pqtwuw5xhbcdbc5gm3m3mvvade

Addressing Churn Prediction Problem with Meta-Heuristic, Machine Learning, Neural Network and Data Mining Techniques: A Case Study of a Telecommunication Company

Abbas Keramati, Ruholla Jafari Marandi
2015 International Journal of Future Computer and Communication  
Using the data of an Iranian mobile company not only these techniques were experienced and were compared to each other, but also we drawn a parallel between some different prominent data mining software  ...  To end, this paper has employed Meta-heuristic, Machine learning, Neural Network and data mining techniques including Genetic Algorithm, Particle Swarm Optimization, Support Vector Machine, Artificial  ...  One can see that data mining techniques, such as Decision Tree, Neural Network, Support vector machine, Bayesian Belief Networks, and Regression, have been prevalently employed in telecommunication customer  ... 
doi:10.18178/ijfcc.2015.4.5.415 fatcat:6hkmq6urqza6tfbzkva66mywia

An Improved Neural Network for Regional Giant Panda Habitat Suitability Mapping: A Case Study in Ya'an Prefecture

Jingwei Song, Xinyuan Wang, Ying Liao, Jing Zhen, Natarajan Ishwaran, Huadong Guo, Ruixia Yang, Chuansheng Liu, Chun Chang, Xin Zong
2014 Sustainability  
In this study, an animal habitat assessment method based on a learning neural network is proposed to reduce the level of subjectivity in animal habitat assessments.  ...  Once the neural network is properly trained, new earth observation data can be integrated for rapid habitat suitability monitoring which could save time and resources needed for traditional data collecting  ...  Author Contributions Jingwei Song and Xinyuan Wang conceived and design the study. JingweiSong and Natarajan Ishwaran performed the experiment and wrote the paper.  ... 
doi:10.3390/su6074059 fatcat:eri536b5iba2phhydjr6cwt6ai

Topic space trajectories

Bastian Schaefermeier, Gerd Stumme, Tom Hanika
2021 Scientometrics  
In addition to a thorough introduction of our method, our focus is on an extensive analysis of the results we achieved.  ...  We show the applicability of our approach on a publication corpus spanning 50 years of machine learning research from 32 publication venues.  ...  Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long  ... 
doi:10.1007/s11192-021-03931-0 fatcat:q6pwpqxa7zb5nmqph6zyw53cpq

Ontology Development for Classification: Spirals - A Case Study in Space Object Classification

Bin Liu, Li Yao, Junfeng Wu, Zheyuan Ding
2017 Proceedings of the 13th International Conference on Web Information Systems and Technologies  
Meanwhile, OBC is more robust than baseline classifiers with respect to a missing feature in the test data.  ...  First, soft sensing data and hard sensing data are collected. Then, various kinds of human knowledge and knowledge obtained by machine learning are combined to build a CO.  ...  OBC Eval outperforms Random Forests, Backpropagation Neural Network, C4.5, SVM, Bayesian Network and Logistic Model Trees, and competes with Ripper.  ... 
doi:10.5220/0006240002250234 dblp:conf/webist/LiuYWD17 fatcat:ct75hba4pzcd7nz74tkrej5yie

Process Prediction in Noisy Data Sets: A Case Study in a Dutch Hospital [chapter]

Sjoerd van der Spoel, Maurice van Keulen, Chintan Amrit
2013 Lecture Notes in Business Information Processing  
In this paper we describe a case study of a Dutch Hospital where we use process mining to predict the cash flow of the Hospital.  ...  In order to predict the cost of a treatment, we use different data mining techniques to predict the sequence of treatments administered, the duration and the final "care product" or diagnosis of the patient  ...  Neural networks are composed of multiple layers of elements that mimic biological neurons, called perceptrons.  ... 
doi:10.1007/978-3-642-40919-6_4 fatcat:ncsupfkqmvhlng4jocscsajh6i

Rainfall and Atmospheric Temperature against the Other Climatic Factors: A Case Study from Colombo, Sri Lanka

Anushka Perera, Upaka Rathnayake
2019 Mathematical Problems in Engineering  
Artificial neural network (ANN) models are developed to define the relationships and then to predict the atmospheric temperature as a function of other parameters including monthly rainfall, minimum and  ...  However, a climate prediction study is yet to be carried out in this tropical climatic zone.  ...  In recent past, soft computing techniques such as Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Interference System (ANFIS), Support vector machines (SVM), Data mining (DM), and Genetic Programming  ... 
doi:10.1155/2019/5692753 fatcat:6e5whqizqjhbzeca65mxmfy5pq

Identification of genetic interaction networks via an evolutionary algorithm evolved Bayesian network

Ruowang Li, Scott M. Dudek, Dokyoon Kim, Molly A. Hall, Yuki Bradford, Peggy L. Peissig, Murray H. Brilliant, James G. Linneman, Catherine A. McCarty, Le Bao, Marylyn D. Ritchie
2016 BioData Mining  
Results: For this study, we present a new algorithm, Grammatical Evolution Bayesian Network (GEBN) that utilizes Bayesian Networks to identify interactions in the data, and at the same time, uses an evolutionary  ...  We were able to identify genetic interactions for T2D cases and controls and use information from those interactions to classify T2D samples.  ...  Network based methods such as Neural Networks [9, 10] and Bayesian Networks [11] use their respective network structures to model interactions.  ... 
doi:10.1186/s13040-016-0094-4 pmid:27168765 pmcid:PMC4862166 fatcat:zvh4qrybtrfghj3r6mlcetfpbq
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