Alternative splicing introduces a new layer of protein diversity and complexity in regulating cellular functions that can be specific to the tissue and cell type, physiological state of a cell, or disease phenotype. I...
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The rapid worldwide decline of wild pollinators over recent years poses a significant environmental threat due to the critical keystone role that pollinators play in terrestrial ecosystems. In order to gain insight in...
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ISBN:
(纸本)9781728158198
The rapid worldwide decline of wild pollinators over recent years poses a significant environmental threat due to the critical keystone role that pollinators play in terrestrial ecosystems. In order to gain insight into the major anthropogenic factors causing these declines, researchers have collected large amounts of ecological data. Yet, they often lack the computational tools needed to analyze the information contained in such datasets. We investigate various data analysis techniques for the Beecology Project, which is a citizen science based effort to rapidly collect data on foraging habits of bumblebee species native to Massachusetts. Different data mining approaches were explored, including association analysis, trend analysis, classification, regression, and clustering. It was found that different techniques were more suitable depending on the biological research question. Future work will focus on making tools utilizing these approaches available online through the Beecology website, where they can be used by the public to determine how best to protect our native pollinators and the diverse ecosystems they support.
Simulation of the electromagnetic response of the human body relies heavily upon efficient computational models or phantoms. The first objective of this paper is to present an improved platform-independent full-body e...
There is a growing interest in measuring the cell wall mechanical property at different locations in single walled cells. We present an inference scheme that maps relative surface elastic modulus distributions along t...
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There is a growing interest in measuring the cell wall mechanical property at different locations in single walled cells. We present an inference scheme that maps relative surface elastic modulus distributions along the cell wall based on tracking the location of material marker points along the turgid and relaxed cell wall outline. A primary scheme is developed to provide a step-function inference of surface elastic moduli by computing the tensions and elastic stretches between material marker points. We perform analysis to investigate the stability of the primary scheme against perturbations on the marker-point locations, which may occur due to image acquisition and processing from experiments. The perturbation analysis shows that the primary scheme is more stable to noise when the spacing between the marker points is coarser, and has been confirmed by the numerical experiments where we apply the primary scheme to synthetic cell outlines from simulations of hyper-elastic membrane deformation with random noise on the marker-point locations. To improve the spatial resolution of elastic modulus distribution of the primary scheme with noise, we propose two optimization schemes that convert the step-function inferences of elastic moduli into smooth-curve inferences. The first optimization scheme infers a canonical elastic modulus distribution based on marker-point locations from multiple cell samples of the same cell type. The second optimization scheme is a simplified cost-effective version that infers the elastic moduli based on marker-point locations from a single cell. The numerical experiments show that the first optimization scheme significantly improves the inference precision for the underlying canonical elastic modulus distributions and can even capture some degree of nonlinearity when the underlying elastic modulus gradients are nonlinear. The second cost-effective scheme is capable of predicting the trend of the elastic modulus gradients *** Cod
For testing a group of hypotheses, tremendous p-value combination methods have been developed and widely applied since 1930's. Some methods (e.g., the minimal p-value) are optimal for sparse signals, and some othe...
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Simulation of the electromagnetic response of the human body relies heavily upon efficient computational models or phantoms. The first objective of this paper is to present an improved platform-independent full-body e...
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Simulation of the electromagnetic response of the human body relies heavily upon efficient computational models or phantoms. The first objective of this paper is to present an improved platform-independent full-body electromagnetic computational model (computational phantom), the Visible Human Project® (VHP)-Female v. 3.1 and to describe its distinct features and enhancements compared to VHP-Female v. 2.0. The second objective is to report phantom simulation for electric stimulation studies using the commercial FEM electromagnetic solver ANSYS MAXWELL.
Simulation of the electromagnetic response of the human body relies heavily upon efficient computational models or phantoms. The first objective of this paper is to present a new platform-independent full-body electro...
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ISBN:
(纸本)9781424492695
Simulation of the electromagnetic response of the human body relies heavily upon efficient computational models or phantoms. The first objective of this paper is to present a new platform-independent full-body electromagnetic computational model (computational phantom), the Visible Human Project? (VHP)-Female v. 2.0 and to describe its distinct features. The second objective is to report phantom simulation performance metrics using the commercial FEM electromagnetic solver ANSYS HFSS.
Muscles consume metabolic energy (ATP) to produce force. A mathematical model for energy expen- diture can be useful in estimating real-time costs of movements or to predict energy optimal movements. Metabolic cost mo...
Macromolecular interactions are formed between proteins, DNA and RNA molecules. Being a principle building block in macromolecular assemblies and pathways, the interactions underlie most of cellular functions. Malfunc...
Macromolecular interactions are formed between proteins, DNA and RNA molecules. Being a principle building block in macromolecular assemblies and pathways, the interactions underlie most of cellular functions. Malfunctioning of macromolecular interactions is also linked to a number of diseases. Structural knowledge of the macromolecular interaction allows one to understand the interaction's mechanism, determine its functional implications and characterize the effects of genetic variations, such as single nucleotide polymorphisms, on the interaction. Unfortunately, until now the interactions mediated by different types of macromolecules, e.g. protein-protein interactions or protein-DNA interactions, are collected into individual and unrelated structural databases. This presents a significant obstacle in the analysis of macromolecular interactions. For instance, the homogeneous structural interaction databases prevent scientists from studying structural interactions of different types but occurring in the same macromolecular complex. Here, we introduce DOMMINO 2.0, a structural Database Of Macro-Molecular INteractiOns. Compared to DOMMINO 1.0, a comprehensive database on protein-protein interactions, DOMMINO 2.0 includes the interactions between all three basic types of macromolecules extracted from PDB files. DOMMINO 2.0 is automatically updated on a weekly basis. It currently includes ∼1 040 000 interactions between two polypeptide subunits (e.g. domains, peptides, termini and interdomain linkers), ∼43 000 RNA-mediated interactions, and ∼12 000 DNA-mediated interactions. All protein structures in the database are annotated using SCOP and SUPERFAMILY family annotation. As a result, protein-mediated interactions involving protein domains, interdomain linkers, C- and N-termini, and peptides are identified. Our database provides an intuitive web interface, allowing one to investigate interactions at three different resolution levels: whole subunit network, binary intera
Evolution and Medicine is a curriculum supplement designed by the National institutes of Health (NIH) and the Biological Sciences Curriculum Study (BSCS) for high school students. The supplement is freely available fr...
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