Ecosyste.ms: Papers

An open API service providing mapping between scientific papers and software projects that are mentioned in them.
All mentions data is based on the CZI Software Mentions dataset.

Projects: pypi: TPOT

https://packages.ecosyste.ms/registries/pypi.org/packages/TPOT

Tree-based Pipeline Optimization Tool
61 versions
Latest release: over 1 year ago
4 dependent packages
37,412 downloads last month

Papers Mentioning TPOT 33

10.1371/journal.pone.0254062
PHOTONAI—A Python API for rapid machine learning model development
Cited by: 8
Author(s): Ramona Leenings, Nils R. Winter, Lucas Plagwitz, Vincent Holstein, Jan Ernsting, Kelvin Sarink, L. Fisch, Jakob Steenweg, Leon Kleine-Vennekate, Julian Gebker, Daniel Emden, Dominik Grotegerd, Nils Opel, Benjamin Risse, Xiaoyi Jiang, Udo Dannlowski, Tim Hahn
Software Mentions: 15
Published: over 3 years ago
10.1186/s12868-019-0538-0
28th Annual Computational Neuroscience Meeting: CNS*2019
Cited by: 3
Author(s):
Software Mentions: 13
Published: about 5 years ago
10.1038/s41598-018-29523-2
Prognostication and Risk Factors for Cystic Fibrosis via Automated Machine Learning
Cited by: 46
Author(s): Ahmed M. Alaa, Mihaela van der Schaar
Software Mentions: 8
Published: over 6 years ago
10.1371/journal.pone.0225577
Designing machine learning workflows with an application to topological data analysis
Cited by: 4
Author(s): Eric Cawi, Patricio S. La Rosa, Arye Nehorai
Software Mentions: 7
Published: almost 5 years ago
10.2196/27344
Discovery of Depression-Associated Factors From a Nationwide Population-Based Survey: Epidemiological Study Using Machine Learning and Network Analysis
Cited by: 9
Author(s): Sang Min Nam, Thomas A Peterson, Kyoung Yul Seo, Hyun Wook Han, Jee In Kang
Software Mentions: 6
Published: over 3 years ago
10.2196/15371
Transfer Learning for Risk Classification of Social Media Posts: Model Evaluation Study
Cited by: 21
Author(s): Derek Howard, Marta M. Maslej, Justin Lee, Jacob Ritchie, Geoffrey Woollard, Leon French
Software Mentions: 5
Published: over 4 years ago
10.1093/bioinformatics/btz796
Model selection for metabolomics: predicting diagnosis of coronary artery disease using automated machine learning
Cited by: 38
Author(s): Alena Orlenko, Daniel Kofink, Leo-Pekka Lyytikäinen, Kjell Nikus, Pashupati P. Mishra, Pekka Kuukasjärvi, Pekka J. Karhunen, Mika Kähönen, Jari Laurikka, Terho Lehtimäki, Folkert W. Asselbergs, Jason H. Moore
Software Mentions: 5
Published: about 5 years ago
10.1038/s41598-021-94696-2
Improving prediction of COVID-19 evolution by fusing epidemiological and mobility data
Cited by: 25
Author(s): Santi García-Cremades, Juan Morales-García, Rocío Hernández-Sanjaime, Raquel Martínez‐España, Andrés Bueno-Crespo, Enrique Hernández-Orallo, José J. López-Espín, José M. Cecilia
Software Mentions: 4
Published: over 3 years ago
10.1002/hbm.25028
An automated machine learning approach to predict brain age from cortical anatomical measures
Cited by: 29
Author(s): Jessica Dafflon, Walter Hugo Lopez Pinaya, Federico Turkheimer, James H. Cole, Robert Leech, Mathew A. Harris, Simon R. Cox, Heather C. Whalley, Andrew M. McIntosh, Peter J. Hellyer
Software Mentions: 4
Published: over 4 years ago
10.1186/s13040-017-0155-3
Ten quick tips for machine learning in computational biology
Cited by: 552
Author(s): Davide Chicco
Software Mentions: 4
Published: almost 7 years ago
10.1371/journal.pcbi.1008390
Ten simple rules for writing a paper about scientific software
Cited by: 1
Author(s): Joseph D. Romano, Jason H. Moore
Software Mentions: 4
Published: about 4 years ago
10.1093/bioinformatics/btz470
Scaling tree-based automated machine learning to biomedical big data with a feature set selector
Cited by: 216
Author(s): Trang T. Le, Weixuan Fu, Jason H. Moore
Software Mentions: 4
Published: over 5 years ago
10.3390/s21134546
Diagnostic of Operation Conditions and Sensor Faults Using Machine Learning in Sucker-Rod Pumping Wells
Cited by: 6
Author(s): João Nascimento, André Laurindo Maitelli, C. W. S. P. Maitelli, Anderson Luiz de Oliveira Cavalcanti
Software Mentions: 4
Published: over 3 years ago
10.1038/s41598-020-73505-2
Germline BRCA 1-2 status prediction through ovarian ultrasound images radiogenomics: a hypothesis generating study (PROBE study)
Cited by: 12
Author(s): Camilla Nero, Francesca Ciccarone, Luca Boldrini, Jacopo Lenkowicz, Ida Paris, Ettore Capoluongo, Antonia Carla Testa, Anna Fagotti, Vincenzo Valentini, Giovanni Scambia
Software Mentions: 4
Published: about 4 years ago
10.1186/s12859-020-03755-4
Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analyses
Cited by: 9
Author(s): Elisabetta Manduchi, Weixuan Fu, Joseph D. Romano, Stefano Ruberto, Jason H. Moore
Software Mentions: 3
Published: about 4 years ago
10.3390/metabo10060243
Machine Learning Applications for Mass Spectrometry-Based Metabolomics
Cited by: 143
Author(s): Ulf W. Liebal, Anh N. Phan, Malvika Sudhakar, Karthik Raman, Lars M. Blank
Software Mentions: 3
Published: over 4 years ago
10.1016/j.patter.2020.100178
SIMON: Open-Source Knowledge Discovery Platform
Cited by: 14
Author(s): Adriana Tomić, Ivan Tomić, Levi Waldron, Ludwig Geistlinger, Max Kühn, Rachel L. Spreng, Lindsay C. Dahora, Kelly E. Seaton, Georgia D. Tomaras, Jennifer Hill, Niharika Arora Duggal, Ross D. Pollock, Norman R. Lazarus, Stephen Harridge, Janet M. Lord, Purvesh Khatri, Andrew J. Pollard, Mark M. Davis
Software Mentions: 3
Published: almost 4 years ago
10.1371/journal.pcbi.1006561
Ten simple rules for documenting scientific software
Cited by: 41
Author(s): Benjamin D. Lee
Software Mentions: 3
Published: almost 6 years ago
10.3389/fncir.2020.00042
Automated Curation of CNMF-E-Extracted ROI Spatial Footprints and Calcium Traces Using Open-Source AutoML Tools
Cited by: 9
Author(s): Lina M. Tran, Andrew J. Mocle, Adam I. Ramsaran, Alexander D. Jacob, Paul W. Frankland, Sheena A. Josselyn
Software Mentions: 3
Published: over 4 years ago
10.1089/cmb.2019.0286
More Accurate Transcript Assembly via Parameter Advising
Cited by: 4
Author(s): Dan DeBlasio, Kwanho Kim, Carl Kingsford
Software Mentions: 3
Published: over 4 years ago
10.1038/s41598-020-76132-z
Differentiation of low and high grade renal cell carcinoma on routine MRI with an externally validated automatic machine learning algorithm
Cited by: 7
Author(s): Subhanik Purkayastha, Yijun Zhao, Jing Wu, Rong Hu, A. McGirr, Sukhdeep Singh, Ken Chang, Raymond Y. Huang, Paul J. Zhang, Alvin Silva, Michael C. Soulen, S. William Stavropoulos, Zishu Zhang, Harrison X. Bai
Software Mentions: 3
Published: about 4 years ago
10.3389/fpsyg.2021.699334
Development and Validation of a Questionnaire to Measure Chinese Preschool Teachers’ Implementation of Social-Emotional Practices
Cited by: 1
Author(s): Li Luo, Patricia Snyder, Yuxi Qiu, Anne Corinne Huggins-Manley, Xiumin Hong
Software Mentions: 2
Published: about 3 years ago
10.1186/s13321-021-00542-y
How can SHAP values help to shape metabolic stability of chemical compounds?
Cited by: 26
Author(s): Agnieszka Wojtuch, Rafał Jankowski, Sabina Podlewska
Software Mentions: 2
Published: about 3 years ago
10.3390/molecules26040777
A Multi-Objective Approach for Drug Repurposing in Preeclampsia
Cited by: 3
Author(s): Eduardo Tejera, Yunierkis Pérez-Castillo, Andrea Chamorro, Alejandro Cabrera-Andrade, Marı́a Eugenia Sánchez
Software Mentions: 2
Published: almost 4 years ago
10.3390/molecules24040743
Machine Learning Approach for Determining the Formation of β-Lactam Antibiotic Complexes with Cyclodextrins Using Multispectral Analysis
Cited by: 5
Author(s): Mikołaj Mizera, Kornelia Lewandowska, Andrzej Miklaszewski, Judyta Cielecka‐Piontek
Software Mentions: 2
Published: almost 6 years ago
10.1371/journal.pone.0241332
Country-level pandemic risk and preparedness classification based on COVID-19 data: A machine learning approach
Cited by: 14
Author(s): Jordan J. Bird, Chloe M. Barnes, Cristiano Premebida, Anikó Ekárt, Diego R. Faria
Software Mentions: 2
Published: about 4 years ago
10.1371/journal.pone.0235179
Examining the effects of transcranial direct current stimulation on human episodic memory with machine learning
Cited by: 7
Author(s): Aleksandra Petrovskaya, Bogdan Kirillov, Anastasiya Asmolova, Giulia Galli, Matteo Feurra, Angela Medvedeva
Software Mentions: 2
Published: almost 4 years ago
10.3389/fpsyt.2020.604478
Brain-Age Prediction Using Shallow Machine Learning: Predictive Analytics Competition 2019
Cited by: 5
Author(s): Pedro F. da Costa, Jessica Dafflon, Walter Hugo Lopez Pinaya
Software Mentions: 2
Published: almost 4 years ago
10.1371/journal.pone.0257850
Optimization of running-in surface morphology parameters based on the AutoML model
Cited by: 0
Author(s): Guangyuan Ge, Fenfen Liu, Gengpei Zhang
Software Mentions: 2
Published: about 3 years ago
10.3390/e23010028
Towards Generative Design of Computationally Efficient Mathematical Models with Evolutionary Learning
Cited by: 10
Author(s): Anna V. Kalyuzhnaya, Nikolay O. Nikitin, Alexander Hvatov, Mikhail Maslyaev, Mikhail Yachmenkov, Alexander V. Boukhanovsky
Software Mentions: 1
Published: almost 4 years ago
10.1038/s41598-020-78611-9
Dysgraphia detection through machine learning
Cited by: 30
Author(s): Peter Drotár, Marek Dobeš
Software Mentions: 1
Published: almost 4 years ago
10.1038/s41598-020-76141-y
The study of automatic machine learning base on radiomics of non-focus area in the first chest CT of different clinical types of COVID-19 pneumonia
Cited by: 19
Author(s): Huibin Tan, Fei Xiong, Yuanliang Jiang, Wencai Huang, Ye Wang, Hanhan Li, Tao You, Tingting Fu, Ran Lu, Biwen Peng
Software Mentions: 1
Published: about 4 years ago
10.3389/fnins.2019.01313
Using Deep Learning and Resting-State fMRI to Classify Chronic Pain Conditions
Cited by: 25
Author(s): Ana Lúcia Almeida Santana, Ignacio Cifré, Charles Novaes de Santana, Pedro Montoya
Software Mentions: 1
Published: almost 5 years ago