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RRegrs: an R package for computer-aided model selection with multiple regression models

Georgia Tsiliki, Cristian R. Munteanu, Jose A. Seoane, Carlos Fernandez-Lozano, Haralambos Sarimveis, Egon L. Willighagen
2015 Journal of Cheminformatics  
Results: We propose an integrated framework for creating multiple regression models, called RRegrs.  ...  The methodology was implemented as an open source R package, available at https://www.github.com/enanomapper/RRegrs, by reusing and extending on the caret package.  ...  Results and discussion RRegrs is an R package for computer-aided model selection, designed and implemented as a collection of regression tools available from the caret package.  ... 
doi:10.1186/s13321-015-0094-2 pmid:26379782 pmcid:PMC4570700 fatcat:be4g7duynvduzmohcztrql4bl4

eNanoMapper applications to support the risk assessment of nanomaterials

Lucian Farcal, Philip Doganis, George Drakakis, Haralambos Sarimveis, Micha Rautenberg, Christoph Helma, Denis Gebele, Nikolay Kochev, Vedrin Jeliazkov, Nina Jeliazkova, Malahat Mousavi, Bengt Fadeel (+11 others)
2017 Zenodo  
To achieve these, eNanoMapper developed an ontology, a data infrastructure and modelling tools with applicability in risk assessment of nanomaterials.  ...  To support a collaborative safety assessment approach an infrastructure for data management was developed, with a database which includes functionalities for data protection, data sharing, data quality  ...  ., RRegrs: an R package for computer-aided model selection with multiple regression models. Journal of Cheminformatics 2015, 7:46.  ... 
doi:10.5281/zenodo.267194 fatcat:e6unbvfxgbckli6rljoapstzde

Predicting Adverse Outcomes in End Stage Renal Disease: Machine Learning Applied to the United States Renal Data System

Zeid Khitan, Alexis D. Jacob, Courtney Balentine, Adam N. Jacob, Juan R. Sanabria, Joseph I. Shapiro
2018 Marshall Journal of Medicine  
RRegrs: an R package for computer-aided model selection with multiple regression models. J Cheminform. 2015;7:46. https://doi.org/10.1186/s13321-015-0094-2 17. Liu R, Li X, Zhang W, Zhou HH.  ...  total) chosen with different randomization seeds to allow for reproducibility. 16 Other packages within R were used for different specific tasks (e.g., NNet for construction of the neural network, randomForest  ...  apply(is.na(dat), 2, all)] # automatically get rid of empty cols at the end #set up outcome variable as "yes" or "no" for subsequent machine learning A=NULL mm=dim(dat1) [ nnet.ROC=roc(response = testset  ... 
doi:10.18590/mjm.2018.vol4.iss4.8 fatcat:osx5vx76enefjdu7clppeev3pi

chemmodlab: a cheminformatics modeling laboratory R package for fitting and assessing machine learning models

Jeremy R Ash, Jacqueline M Hughes-Oliver
2018 Journal of Cheminformatics  
The goal of chemmodlab is to streamline the fitting and assessment pipeline for many machine learning models in R, making it easy for researchers to compare the utility of these models.  ...  The most novel feature of chemmodlab is the ease with which statistically significant performance differences for many machine learning models is presented by means of the multiple comparisons similarity  ...  A subset of this AID 364 data set is also provided with the chemmodlab package on CRAN [3]. The bpdata data set is provided with the rcdk package on CRAN [17].  ... 
doi:10.1186/s13321-018-0309-4 pmid:30488298 pmcid:PMC6755574 fatcat:yqqcass35rehta3bt4vbvnfiru

Towards reproducible computational drug discovery

Nalini Schaduangrat, Samuel Lampa, Saw Simeon, Matthew Paul Gleeson, Ola Spjuth, Chanin Nantasenamat
2020 Journal of Cheminformatics  
.), (3) science of reproducible research (i.e. comparison and contrast with related concepts as replicability, reusability and reliability), (4) model development in computational drug discovery, (5) computational  ...  issues on model development and deployment, (6) use case scenarios for streamlining the computational drug discovery protocol.  ...  Likit Preeyanon from the Department of Community Medical Technology for fruitful discussions.  ... 
doi:10.1186/s13321-020-0408-x pmid:33430992 fatcat:bvdcvjhi4jhlnifpc25t6cjthq

Molecular Recipe for γ-Secretase Modulation from Computational Analysis of 60 Active Compounds

Ning Tang, Arun K. Somavarapu, Kasper P. Kepp
2018 ACS Omega  
Our results may aid the development of new γ-secretase modulators with optimal hydrogen bonds, shape, and hydrophobicity but more importantly provide a structural−chemical model of the modulation of Aβ  ...  Our model suggests that many molecules can modulate cleavage simply by contributing their binding energy to stabilize the compact ternary complex with C99.  ...  These methods were applied using a wrapper package called RRegrs in R, 42 using the standard parameters.  ... 
doi:10.1021/acsomega.8b02196 fatcat:gvlyus6gcrgbxpmez675s7j3qu

Robust Analysis of Linear Models

Joseph W. McKean
2004 Statistical Science  
linear models.  ...  This paper presents three lectures on a robust analysis of linear models.  ...  Recently, Terpstra and McKean (2004) developed packages of R and SPLUS functions which compute these procedures for the Wilcoxon and the high breakdown estimates.  ... 
doi:10.1214/088342304000000549 fatcat:nq3zgg74zbeetdriwy2sdltl2a

NanoSolveIT Project: Driving Nanoinformatics research to develop innovative and integrated tools for in silico nanosafety assessment

Antreas Afantitis, Georgia Melagraki, Panagiotis Isigonis, Andreas Tsoumanis, Dimitra Danai Varsou, Eugenia Valsami-Jones, Anastasios Papadiamantis, Laura-Jayne.A Ellis, Haralambos Sarimveis, Philip Doganis, Pantelis Karatzas, Periklis Tsiros (+41 others)
2020 Computational and Structural Biotechnology Journal  
Integration of such extensive NM information sources with the latest nanoinformatics methods will allow NanoSolveIT to model the relationships between NM structure (morphology), properties and their adverse  ...  Here, the available NM libraries are analyzed for their suitability for integration with novel nanoinformatics approaches and for the development of NM specific Integrated Approaches to Testing and Assessment  ...  RRegrs R package [169] .  ... 
doi:10.1016/j.csbj.2020.02.023 pmid:32226594 pmcid:PMC7090366 fatcat:ng6flbglv5c73ejegdoiuspagm

NanoSolveIT Project: driving Nanoinformatics research to develop innovative and integrated tools for in silico nanosafety assessment

Antreas Afantitis, Georgia Melagraki, Panagiotis Isigonis, Andreas Tsoumanis, Dimitra Danai Varsou, Eugenia Valsami-Jones, Anastasios Papadiamantis, Laura-Jayne A Ellis, Haralambos Sarimveis, Philip Doganis, Pantelis Karatzas, Periklis Tsiros (+41 others)
2021
Integration of such extensive NM information sources with the latest nanoinformatics methods will allow NanoSolveIT to model the relationships between NM structure (morphology), properties and their adverse  ...  Here, the available NM libraries are analyzed for their suitability for integration with novel nanoinformatics approaches and for the development of NM specific Integrated Approaches to Testing and Assessment  ...  RRegrs R package [169] .  ... 
doi:10.26181/60e3d49edbed7 fatcat:mt5yqx3qtfhnbfor2jj3domfra