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Towards a Quantitative Understanding of Cell Identity.
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Macromolecular crowding: chemistry and physics meet biology (Ascona, Switzerland, 10-14 June 2012).
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The evolving concept of cell identity in the single cell era.
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Inferring fitness landscapes and selection on phenotypic states from single-cell genealogical data.
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Computational systems biology and dose-response modeling in relation to new directions in toxicity testing.
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Computational modeling of drug response with applications to neuroscience.
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Discovering collectively informative descriptors from high-throughput experiments.
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Single-cell network biology for resolving cellular heterogeneity in human diseases.
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The future of Cochrane Neonatal.
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Transiently increased coordination in gene regulation during cell phenotypic transitions.
PRX Life. 2024 Dec;2(4). doi: 10.1103/prxlife.2.043009. Epub 2024 Nov 5.
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Inertial effect of cell state velocity on the quiescence-proliferation fate decision.
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Decoding Human Biology and Disease Using Single-cell Omics Technologies.
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Complex computation from developmental priors.
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Mid-Infrared Photothermal-Fluorescence In Situ Hybridization for Functional Analysis and Genetic Identification of Single Cells.
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Learning cell identity in immunology, neuroscience, and cancer.
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Assessment and Optimization of Explainable Machine Learning Models Applied to Transcriptomic Data.
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本文引用的文献

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A comparison of single-cell trajectory inference methods.
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Multiplexed protein maps link subcellular organization to cellular states.
Science. 2018 Aug 3;361(6401). doi: 10.1126/science.aar7042.
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Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics.
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Cell type atlas and lineage tree of a whole complex animal by single-cell transcriptomics.
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Highly scalable generation of DNA methylation profiles in single cells.
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Simultaneous lineage tracing and cell-type identification using CRISPR-Cas9-induced genetic scars.
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Reconstruction of complex single-cell trajectories using CellRouter.
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Reversed graph embedding resolves complex single-cell trajectories.
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Not just a colourful metaphor: modelling the landscape of cellular development using Hopfield networks.
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