13 results on '"Nelson, Philip C."'
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2. Colloidal particle motion as a diagnostic of DNA conformational transitions
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Nelson, Philip C.
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NUCLEIC acids , *DNA , *GENES , *THICKNESS measurement - Abstract
Abstract: Tethered particle motion is an experimental technique to monitor conformational changes in single molecules of DNA in real time, by observing the position fluctuations of a micrometer-size particle attached to the DNA. This article reviews some recent work on theoretical problems inherent in the interpretation of TPM experiments, both in equilibrium and dynamical aspects. [Copyright &y& Elsevier]
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- 2007
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3. Teaching Biological Physics.
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Goldstein, Raymond E., Nelson, Philip C., and Powers, Thomas R.
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BIOPHYSICS education , *CURRICULUM , *CURRICULUM planning , *SOFT condensed matter , *PHYSICS education (Higher) - Abstract
Examines the reasons behind the difficulty of creating and sustaining courses for biological physics and offers some ideas for planning such courses. Obstacles to creating biological physics courses; Way to incorporate experiments in biological physics and soft condensed matter physics into the curriculum; Strategies for designing a course for students with no university-level physics experience.
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- 2005
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4. Spare the (Elastic) Rod.
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Nelson, Philip C.
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BIOCHEMICAL research , *ELASTICITY , *MOLECULAR dynamics , *DNA folding , *DNA analysis , *LINEAR systems - Abstract
The article discusses a report within the issue regarding biochemistry research by R. Vafabakhsh and T. Ha. The author notes that findings from Vafabakhsh and Ha's study provide the clearest evidence yet that the elastic-rod model for DNA mechanics, which is an emergent description that works well on long length scales, breaks down on shorter length scales when applied to cell biology. Topics include the concept of emergence, which is a function of increasing length scale, research by Jonathan Widom investigating whether DNA could be regarded as a linearly elastic rod, and a diagram showing biological examples of tightly bent DNA.
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- 2012
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5. A Demonstration of the Infrared Activity of Carbon Dioxide.
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Sieg, Philip G., Berner, William, Harnish, Peter K., and Nelson, Philip C.
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CARBON dioxide , *INFRARED testing , *PHYSICS students , *PHYSICS education , *VIBRATIONAL spectra - Abstract
Climate is a topic of great concern to students, but it remains difficult to discuss scientifically. We are bombarded daily by emotional messaging for and against the proposition that human activities are altering the climate in ways that may have catastrophic effects. But it often seems that those predictions rest entirely on massive computer simulation models, which the listener is not in a position to evaluate. We wished to find an aspect of the puzzle that could be directly experienced, and that would therefore give us a solid starting point for discussion. Here we describe a dramatic lecture demonstration that scales well for large audiences and that requires as little as 10 classroom minutes to show an important difference between room air and carbon dioxide gas. Beyond its significance for public policy, the demonstration can serve as a springboard to motivate discussion of important physics concepts such as molecular rotation and vibration spectra. [ABSTRACT FROM AUTHOR]
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- 2019
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6. Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.
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Gulshan, Varun, Peng, Lily, Coram, Marc, Stumpe, Martin C., Wu, Derek, Narayanaswamy, Arunachalam, Venugopalan, Subhashini, Widner, Kasumi, Madams, Tom, Cuadros, Jorge, Kim, Ramasamy, Raman, Rajiv, Nelson, Philip C., Mega, Jessica L., and Webster, Dale R.
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DIABETIC retinopathy , *DEEP learning , *MEDICAL technology , *DIGITAL diagnostic imaging , *OPHTHALMOSCOPY , *DIAGNOSIS , *ALGORITHMS , *COMPARATIVE studies , *RESEARCH methodology , *MEDICAL cooperation , *ARTIFICIAL neural networks , *PHOTOGRAPHY , *RESEARCH , *RETINA , *RETINAL degeneration , *EVALUATION research , *RESEARCH bias - Abstract
Importance: Deep learning is a family of computational methods that allow an algorithm to program itself by learning from a large set of examples that demonstrate the desired behavior, removing the need to specify rules explicitly. Application of these methods to medical imaging requires further assessment and validation.Objective: To apply deep learning to create an algorithm for automated detection of diabetic retinopathy and diabetic macular edema in retinal fundus photographs.Design and Setting: A specific type of neural network optimized for image classification called a deep convolutional neural network was trained using a retrospective development data set of 128 175 retinal images, which were graded 3 to 7 times for diabetic retinopathy, diabetic macular edema, and image gradability by a panel of 54 US licensed ophthalmologists and ophthalmology senior residents between May and December 2015. The resultant algorithm was validated in January and February 2016 using 2 separate data sets, both graded by at least 7 US board-certified ophthalmologists with high intragrader consistency.Exposure: Deep learning-trained algorithm.Main Outcomes and Measures: The sensitivity and specificity of the algorithm for detecting referable diabetic retinopathy (RDR), defined as moderate and worse diabetic retinopathy, referable diabetic macular edema, or both, were generated based on the reference standard of the majority decision of the ophthalmologist panel. The algorithm was evaluated at 2 operating points selected from the development set, one selected for high specificity and another for high sensitivity.Results: The EyePACS-1 data set consisted of 9963 images from 4997 patients (mean age, 54.4 years; 62.2% women; prevalence of RDR, 683/8878 fully gradable images [7.8%]); the Messidor-2 data set had 1748 images from 874 patients (mean age, 57.6 years; 42.6% women; prevalence of RDR, 254/1745 fully gradable images [14.6%]). For detecting RDR, the algorithm had an area under the receiver operating curve of 0.991 (95% CI, 0.988-0.993) for EyePACS-1 and 0.990 (95% CI, 0.986-0.995) for Messidor-2. Using the first operating cut point with high specificity, for EyePACS-1, the sensitivity was 90.3% (95% CI, 87.5%-92.7%) and the specificity was 98.1% (95% CI, 97.8%-98.5%). For Messidor-2, the sensitivity was 87.0% (95% CI, 81.1%-91.0%) and the specificity was 98.5% (95% CI, 97.7%-99.1%). Using a second operating point with high sensitivity in the development set, for EyePACS-1 the sensitivity was 97.5% and specificity was 93.4% and for Messidor-2 the sensitivity was 96.1% and specificity was 93.9%.Conclusions and Relevance: In this evaluation of retinal fundus photographs from adults with diabetes, an algorithm based on deep machine learning had high sensitivity and specificity for detecting referable diabetic retinopathy. Further research is necessary to determine the feasibility of applying this algorithm in the clinical setting and to determine whether use of the algorithm could lead to improved care and outcomes compared with current ophthalmologic assessment. [ABSTRACT FROM AUTHOR]- Published
- 2016
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7. Transformation of Stimulus Correlations by the Retina.
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Simmons, Kristina D., Prentice, Jason S., Tkačik, Gašper, Homann, Jan, Yee, Heather K., Palmer, Stephanie E., Nelson, Philip C., and Balasubramanian, Vijay
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STIMULUS & response (Biology) , *SENSORY neurons , *RETINAL ganglion cells , *WHITE noise , *NEUROSCIENCES , *NONLINEAR theories - Abstract
Redundancies and correlations in the responses of sensory neurons may seem to waste neural resources, but they can also carry cues about structured stimuli and may help the brain to correct for response errors. To investigate the effect of stimulus structure on redundancy in retina, we measured simultaneous responses from populations of retinal ganglion cells presented with natural and artificial stimuli that varied greatly in correlation structure; these stimuli and recordings are publicly available online. Responding to spatio-temporally structured stimuli such as natural movies, pairs of ganglion cells were modestly more correlated than in response to white noise checkerboards, but they were much less correlated than predicted by a non-adapting functional model of retinal response. Meanwhile, responding to stimuli with purely spatial correlations, pairs of ganglion cells showed increased correlations consistent with a static, non-adapting receptive field and nonlinearity. We found that in response to spatio-temporally correlated stimuli, ganglion cells had faster temporal kernels and tended to have stronger surrounds. These properties of individual cells, along with gain changes that opposed changes in effective contrast at the ganglion cell input, largely explained the pattern of pairwise correlations across stimuli where receptive field measurements were possible. [ABSTRACT FROM AUTHOR]
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- 2013
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8. The Syncytial Drosophila Embryo as a Mechanically Excitable Medium.
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Idema, Timon, Dubuis, Julien O., Kang, Louis, Manning, M. Lisa, Nelson, Philip C., Lubensky, Tom C., and Liu, Andrea J.
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DROSOPHILA , *MITOSIS , *INSECT embryology , *CONFOCAL microscopy , *CELL cycle , *METAPHASE (Mitosis) , *IMAGE analysis , *INSECTS - Abstract
Mitosis in the early syncytial Drosophila embryo is highly correlated in space and time, as manifested in mitotic wavefronts that propagate across the embryo. In this paper we investigate the idea that the embryo can be considered a mechanically-excitable medium, and that mitotic wavefronts can be understood as nonlinear wavefronts that propagate through this medium. We study the wavefronts via both image analysis of confocal microscopy videos and theoretical models. We find that the mitotic waves travel across the embryo at a well-defined speed that decreases with replication cycle. We find two markers of the wavefront in each cycle, corresponding to the onsets of metaphase and anaphase. Each of these onsets is followed by displacements of the nuclei that obey the same wavefront pattern. To understand the mitotic wavefronts theoretically we analyze wavefront propagation in excitable media. We study two classes of models, one with biochemical signaling and one with mechanical signaling. We find that the dependence of wavefront speed on cycle number is most naturally explained by mechanical signaling, and that the entire process suggests a scenario in which biochemical and mechanical signaling are coupled. [ABSTRACT FROM AUTHOR]
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- 2013
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9. Fast, Scalable, Bayesian Spike Identification for Multi- Electrode Arrays.
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Prentice, Jason S., Homann, Jan, Simmons, Kristina D., Tkačik, Gašper, Balasubramanian, Vijay, and Nelson, Philip C.
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BAYESIAN analysis , *SPATIAL ability , *BIOPHYSICS , *SOCIAL interaction , *CELLULAR signal transduction , *GUINEA pigs as laboratory animals , *RETINAL ganglion cells - Abstract
We present an algorithm to identify individual neural spikes observed on high-density multi-electrode arrays (MEAs). Our method can distinguish large numbers of distinct neural units, even when spikes overlap, and accounts for intrinsic variability of spikes from each unit. As MEAs grow larger, it is important to find spike-identification methods that are scalable, that is, the computational cost of spike fitting should scale well with the number of units observed. Our algorithm accomplishes this goal, and is fast, because it exploits the spatial locality of each unit and the basic biophysics of extracellular signal propagation. Human interaction plays a key role in our method; but effort is minimized and streamlined via a graphical interface. We illustrate our method on data from guinea pig retinal ganglion cells and document its performance on simulated data consisting of spikes added to experimentally measured background noise. We present several tests demonstrating that the algorithm is highly accurate: it exhibits low error rates on fits to synthetic data, low refractory violation rates, good receptive field coverage, and consistency across users. [ABSTRACT FROM AUTHOR]
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- 2011
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10. Concentration and Length Dependence of DNA Looping in Transcriptional Regulation.
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Lin Han, Garcia, Hernan G., Blumberg, Seth, Towles, Kevin B., Beausang, John F., Nelson, Philip C., and Phillips, Rob
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TRANSCRIPTION factors , *BINDING sites , *PROTEIN binding , *GENETIC regulation , *PROMOTERS (Genetics) , *DNA , *PROKARYOTES , *EUKARYOTIC cells - Abstract
In many cases, transcriptional regulation involves the binding of transcription factors at sites on the DNA that are not immediately adjacent to the promoter of interest. This action at a distance is often mediated by the formation of DNA loops: Binding at two or more sites on the DNA results in the formation of a loop, which can bring the transcription factor into the immediate neighborhood of the relevant promoter. These processes are important in settings ranging from the historic bacterial examples (bacterial metabolism and the lytic-lysogeny decision in bacteriophage), to the modern concept of gene regulation to regulatory processes central to pattern formation during development of multicellular organisms. Though there have been a variety of insights into the combinatorial aspects of transcriptional control, the mechanism of DNA looping as an agent of combinatorial control in both prokaryotes and eukaryotes remains unclear. We use single-molecule techniques to dissect DNA looping in the lac operon. In particular, we measure the propensity for DNA looping by the Lac repressor as a function of the concentration of repressor protein and as a function of the distance between repressor binding sites. As with earlier single-molecule studies, we find (at least) two distinct looped states and demonstrate that the presence of these two states depends both upon the concentration of repressor protein and the distance between the two repressor binding sites. We find that loops form even at interoperator spacings considerably shorter than the DNA persistence length, without the intervention of any other proteins to prebend the DNA. The concentration measurements also permit us to use a simple statistical mechanical model of DNA loop formation to determine the free energy of DNA looping, or equivalently, the J-factor for looping. [ABSTRACT FROM AUTHOR]
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- 2009
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11. The role of microtubule movement in bidirectional organelle transport.
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Kulić, Igor M., Brown, André E. X., Hwajin Kim, Kural, Comert, Blehm, Benjamin, Selvin, Paul R., Nelson, Philip C., and Gelfand, Vladimir I.
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MICROTUBULES , *DROSOPHILA , *PEROXISOMES , *CYTOSKELETAL proteins , *OSCILLATIONS - Abstract
We study the role of microtubule movement in bidirectional organelle transport in Drosophila S2 cells and show that EGFP- tagged peroxisomes in cells serve as sensitive probes of motor induced, noisy cytoskeletal motions. Multiple peroxisomes move in unison over large time windows and show correlations with microtubule tip positions, indicating rapid microtubule fluctuations in the longitudinal direction. We report the first high-resolution measurement of longitudinal microtubule fluctuations per- formed by tracing such pairs of co-moving peroxisomes. The resulting picture shows that motor-dependent longitudinal micro- tubule oscillations contribute significantly to cargo movement along microtubules. Thus, contrary to the conventional view. organelle transport cannot be described solely in terms of cargo movement along stationary microtubule tracks, but instead includes a strong contribution from the movement of the tracks. [ABSTRACT FROM AUTHOR]
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- 2008
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12. Elementary simulation of tethered Brownian motion.
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Beausang, John F., Zurla, Chiara, Finzi, Laura, Sullivan, Luke, and Nelson, Philip C.
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WIENER processes , *SIMULATION methods & models , *PARTICLES (Nuclear physics) , *BIOPHYSICS , *THERMODYNAMIC equilibrium , *MOTION - Abstract
We describe a simple simulation, suitable for an undergraduate project or graduate problem set, of the Brownian motion of a particle in a Hooke's law potential well. Understanding this physical situation is necessary in many experimental contexts, for instance in single molecule biophysics, and its simulation helps students appreciate the dynamical character of thermal equilibrium. The simulation captures behavior seen in experimental data on tethered particle motion. [ABSTRACT FROM AUTHOR]
- Published
- 2007
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13. High flexibility of DNA on short length scales probed by atomic force microscopy.
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Wiggins, Paul A., van der Heijden, Thijn, Moreno-Herrero, Fernando, Spakowitz, Andrew, Phillips, Rob, Widom, Jonathan, Dekker, Cees, and Nelson, Philip C.
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ATOMIC force microscopy , *ELASTICITY , *BIOMECHANICS , *DNA , *BENDING stresses , *CELL physiology - Abstract
The mechanics of DNA bending on intermediate length scales (5–100 nm) plays a key role in many cellular processes, and is also important in the fabrication of artificial DNA structures, but previous experimental studies of DNA mechanics have focused on longer length scales than these. We use high-resolution atomic force microscopy on individual DNA molecules to obtain a direct measurement of the bending energy function appropriate for scales down to 5 nm. Our measurements imply that the elastic energy of highly bent DNA conformations is lower than predicted by classical elasticity models such as the worm-like chain (WLC) model. For example, we found that on short length scales, spontaneous large-angle bends are many times more prevalent than predicted by the WLC model. We test our data and model with an interlocking set of consistency checks. Our analysis also shows how our model is compatible with previous experiments, which have sometimes been viewed as confirming the WLC. [ABSTRACT FROM AUTHOR]
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- 2006
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