Repeated Decision Stumping Distils Simple Rules from Single Cell Data
暂无分享,去创建一个
[1] K. Parain,et al. A large scale screen for neural stem cell markers in Xenopus retina , 2012, Developmental neurobiology.
[2] Michael P. H. Stumpf,et al. Learning regulatory models for cell development from single cell transcriptomic data , 2017 .
[3] Sarah Filippi,et al. Information theory and signal transduction systems: from molecular information processing to network inference. , 2014, Seminars in cell & developmental biology.
[4] Tso-Jung Yen,et al. Discussion on "Stability Selection" by Meinshausen and Buhlmann , 2010 .
[5] Casper Kaae Sønderby,et al. scVAE: variational auto-encoders for single-cell gene expression data , 2020, Bioinform..
[6] M. Stumpf,et al. Transition State Characteristics During Cell Differentiation , 2018, bioRxiv.
[7] Sui Huang. The Tension Between Big Data and Theory in the "Omics" Era of Biomedical Research , 2019, Perspectives in biology and medicine.
[8] Jason M. Klusowski. Sparse learning with CART , 2020, NeurIPS.
[9] S. Pierce,et al. Regulation of Spemann organizer formation by the intracellular kinase Xgsk-3. , 1995, Development.
[10] H. Débat,et al. TopA, the Sulfolobus solfataricus topoisomerase III, is a decatenase , 2017, Nucleic acids research.
[11] Christian P. Robert,et al. Large-scale inference , 2010 .
[12] Thalia E. Chan,et al. Gene Regulatory Network Inference from Single-Cell Data Using Multivariate Information Measures , 2016, bioRxiv.
[13] G. La Manno,et al. The emergence and promise of single-cell temporal-omics approaches. , 2020, Current opinion in biotechnology.
[14] Rudiyanto Gunawan,et al. Single-Cell-Based Analysis Highlights a Surge in Cell-to-Cell Molecular Variability Preceding Irreversible Commitment in a Differentiation Process , 2016, PLoS biology.
[15] Matthias Hein,et al. Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks , 2019, NeurIPS.
[16] Ying Wang,et al. Xenbase: a genomic, epigenomic and transcriptomic model organism database , 2017, Nucleic Acids Res..
[17] M. Stumpf,et al. Systems biology (un)certainties , 2015, Science.
[18] John Lygeros,et al. Iterative experiment design guides the characterization of a light-inducible gene expression circuit , 2015, Proceedings of the National Academy of Sciences.
[19] M. Khammash,et al. A universal biomolecular integral feedback controller for robust perfect adaptation , 2019, Nature.
[20] Thomas M. Cover,et al. Elements of Information Theory: Cover/Elements of Information Theory, Second Edition , 2005 .
[21] Robert C. Holte,et al. Very Simple Classification Rules Perform Well on Most Commonly Used Datasets , 1993, Machine Learning.
[22] Michael P H Stumpf,et al. Control mechanisms for stochastic biochemical systems via computation of reachable sets , 2016, bioRxiv.
[23] J. Marioni,et al. Using single‐cell genomics to understand developmental processes and cell fate decisions , 2018, Molecular systems biology.
[24] Diogo M. Camacho,et al. Next-Generation Machine Learning for Biological Networks , 2018, Cell.
[25] Kevin P. Murphy,et al. Machine learning - a probabilistic perspective , 2012, Adaptive computation and machine learning series.
[26] Patrick S. Stumpf,et al. Stem Cell Differentiation as a Non-Markov Stochastic Process , 2017, Cell systems.
[27] D. Ruppert. The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2004 .
[28] Alistair A. Young,et al. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , 2017, MICCAI 2017.
[29] Kui Wang,et al. Deep learning enables accurate clustering with batch effect removal in single-cell RNA-seq analysis , 2020, Nature Communications.
[30] Austin G Smith,et al. Conversion of embryonic stem cells into neuroectodermal precursors in adherent monoculture , 2003, Nature Biotechnology.
[31] Allon M. Klein,et al. The dynamics of gene expression in vertebrate embryogenesis at single-cell resolution , 2018, Science.
[32] Martin Vingron,et al. Gene expression screening in Xenopus identifies molecular pathways, predicts gene function and provides a global view of embryonic patterning , 1998, Mechanisms of Development.
[33] R. Satija,et al. Integrative single-cell analysis , 2019, Nature Reviews Genetics.
[34] N. Gao,et al. Universality of cell differentiation trajectories revealed by a reconstruction of transcriptional uncertainty landscapes from single-cell transcriptomic data , 2020, bioRxiv.
[35] John J Tyson,et al. A Dynamical Paradigm for Molecular Cell Biology. , 2020, Trends in cell biology.
[36] Michael P H Stumpf,et al. An information-theoretic framework for deciphering pleiotropic and noisy biochemical signaling , 2018, Nature Communications.
[37] Qing Nie,et al. Cell lineage and communication network inference via optimization for single-cell transcriptomics , 2019, Nucleic acids research.
[38] J. Ross Quinlan,et al. Induction of Decision Trees , 1986, Machine Learning.
[39] Hong Qian,et al. Processes on the emergent landscapes of biochemical reaction networks and heterogeneous cell population dynamics: differentiation in living matters , 2017, Journal of The Royal Society Interface.
[40] Thomas M. Cover,et al. Elements of Information Theory , 2005 .
[41] Robert C. Holte,et al. Decision Tree Instability and Active Learning , 2007, ECML.
[42] R. Aebersold,et al. Proteomic and interactomic insights into the molecular basis of cell functional diversity , 2020, Nature Reviews Molecular Cell Biology.
[43] Michael P H Stumpf,et al. Transition state characteristics during cell differentiation , 2018, bioRxiv.
[44] Allon M. Klein,et al. Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells , 2015, Cell.
[45] L. Goentoro,et al. Two-Element Transcriptional Regulation in the Canonical Wnt Pathway , 2017, Current Biology.
[46] PAUL KIRK,et al. Balancing the Robustness and Predictive Performance of Biomarkers , 2013, J. Comput. Biol..
[47] Heather A. Harrington,et al. Cellular compartments cause multistability and allow cells to process more information. , 2013, Biophysical journal.
[48] Li Zhong,et al. Murine embryonic stem cell differentiation is promoted by SOCS-3 and inhibited by the zinc finger transcription factor Klf4. , 2005, Blood.
[49] M. Hemberg,et al. Challenges in unsupervised clustering of single-cell RNA-seq data , 2019, Nature Reviews Genetics.
[50] Elizabeth H. Peuchen,et al. Phosphorylation Dynamics Dominate the Regulated Proteome during Early Xenopus Development , 2017, Scientific Reports.
[51] A. M. Arias,et al. Transition states and cell fate decisions in epigenetic landscapes , 2016, Nature Reviews Genetics.
[52] N. Meinshausen,et al. Stability selection , 2008, 0809.2932.
[53] Alexey M. Kozlov,et al. Eleven grand challenges in single-cell data science , 2020, Genome Biology.
[54] D. Lubahn,et al. ERRβ: A potent inhibitor of Nrf2 transcriptional activity , 2007, Molecular and Cellular Endocrinology.