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Testing Precision Limits of Neural Network-Based Quality Control Metrics in High-Throughput Digital Microscopy.
- Published in:
- Pharmaceutical Research, 2022, v. 39, n. 2, p. 263, doi. 10.1007/s11095-021-03130-9
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- Article
Inferring Latent States and Refining Force Estimates via Hierarchical Dirichlet Process Modeling in Single Particle Tracking Experiments.
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- PLoS ONE, 2015, v. 10, n. 9, p. 1, doi. 10.1371/journal.pone.0137633
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- Article
Supervised and unsupervised machine learning approaches for monitoring subvisible particles within an aluminum‐salt adjuvanted vaccine formulation.
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- Biotechnology & Bioengineering, 2024, v. 121, n. 5, p. 1626, doi. 10.1002/bit.28671
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- Article
Machine learning approaches to root cause analysis, characterization, and monitoring of subvisible particles in monoclonal antibody formulations.
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- Biotechnology & Bioengineering, 2022, v. 119, n. 12, p. 3596, doi. 10.1002/bit.28239
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- Article
Machine learning and statistical analyses for extracting and characterizing "fingerprints" of antibody aggregation at container interfaces from flow microscopy images.
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- Biotechnology & Bioengineering, 2020, v. 117, n. 11, p. 3322, doi. 10.1002/bit.27501
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- Article
Analyzing single-molecule manipulation experiments.
- Published in:
- Journal of Molecular Recognition, 2009, v. 22, n. 5, p. 356, doi. 10.1002/jmr.959
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- Article
Correction: Calderon, C.P. Data-Driven Techniques for Detecting Dynamical State Changes in Noisily Measured 3D Single-Molecule Trajectories. Molecules 19, 18381-18398.
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- 2015
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- Correction Notice
Data-Driven Techniques for Detecting Dynamical State Changes in Noisily Measured 3D Single-Molecule Trajectories.
- Published in:
- Molecules, 2014, v. 19, n. 11, p. 18381, doi. 10.3390/molecules191118381
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- Publication type:
- Article