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SSRN 2020年

作者： Narykov, Oleksandr Johnson, Nathan Korkin, Dmitry Department of Computer Science Bioinformatics and Computational Biology Program Worcester Polytechnic Institute WorcesterMA United States Harvard Program in Therapeutic Sciences Harvard Medical School Breast Tumor Immunology Laboratory Dana-Farber Cancer Institute BostonMA United States Department of Computer Science Bioinformatics and Computational Biology Program Worcester Polytechnic Institute WorcesterMA United States

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. In particular, recent high-throughput experimental studies have illuminated the functional role of splicing events through rewiring protein-protein interactions, yet the extent to which the macromolecular interactions are affected by alternative splicing has to be fully understood. In silico methods provide a fast and cheap alternative to interrogating functional characteristics of thousands of alternatively spliced isoforms. Here we develop an accurate feature-based machine learning approach that predicts if a protein-protein interaction carried out by a reference isoform is perturbed by an alternatively spliced isoform. Our method called ALTernatively Spliced INteractions prediction (ALT-IN) Tool was compared with the state-of-the-art PPI prediction tools and showed superior performance, achieving 0.92 in precision and recall values. © 2020, The Authors. All rights reserved.

关键词： Forecasting

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Investigating the Efficacy of Data Mining Techniques for Crowdsourced Biological Datasets

Investigating the Efficacy of Data Mining Techniques for Cro...

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IEEE MIT Undergraduate Research Technology Conference (URTC)

作者： Ilona Regan Dany Alkurdi Sarun Paisarnsrisomsuk Carolina Ruiz Elizabeth F. Ryder Rob Gegear Bioinformatics and Computational Biology Program Worcester Polytechnic Institute Worcester MA USA Princeton University Princeton NJ USA Worcester Polytechnic Institute Worcester MA USA University of Massachusetts Dartmouth Dartmouth MA USA

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.

关键词： Data analysis Conferences Ecosystems Market research Encoding Data mining Biological information theory

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VHP-Female full-body human CAD model for cross-platform FEM simulations - Recent development and validations 38

VHP-Female full-body human CAD model for cross-platform FEM ...

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38th Annual International Conference of the IEEE Engineering in Medicine and biology Society, EMBC 2016

作者： Tankaria, Harshal Jackson, Xavier J. Borwankar, Raunak Srichandhru, Goutham N. K. Le Tran, Anh Yanamadala, Janakinadh Noetscher, Gregory M. Nazarian, Ara Louie, Sara Makarov, Sergey N. Electrical and Computer Eng. Dept. at Worcester Polytechnic Institute WorcesterMA01604 United States Bioinformatics and Computational Biology Dept. at Worcester Polytechnic Institute WorcesterMA01604 United States Center for Advanced Orthopaedic Studies at Beth Israel Deaconess Medical Center Harvard Med. School BostonMA United States ANSYS Inc. CanonsburgPA United States

ISBN: (纸本)9781457702204

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. © 2016 IEEE.

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Inferring relative surface elastic moduli in thin-wall models of single cells

arXiv

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arXiv 2022年

作者： Deng, Yaqi Wei, Chaozhen Xu, Rholee Vidali, Luis Wu, Min Life Sciences Imperial College London LondonSW7 2AZ United Kingdom Mathematical Sciences Worcester Polytechnic Institute WorcesterMA01609 United States Bioinformatics and Computational Biology Worcester Polytechnic Institute WorcesterMA01609 United States Biology and Biotechnology Worcester Polytechnic Institute WorcesterMA01609 United States

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

关键词： Elastic moduli

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TFisher tests: Optimal and adaptive thresholding for combining p-values

arXiv

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arXiv 2018年

作者： Zhang, Hong Tong, Tiejun Landers, John Wu, Zheyang Department of Mathematical Sciences Worcester Polytechnic Institute WorcesterMA01609 United States Department of Mathematics Hong Kong Baptist University Kowloon Tong Hong Kong Department of Neurology University of Massachusetts Medical School WorcesterMA01655 United States Department of Mathematical Sciences Program of Bioinformatics and Computational Biology Program of Data Science Worcester Polytechnic Institute WorcesterMA01609 United States

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 others (e.g., Fisher's combination) are optimal for dense signals. To address a wide spectrum of signal patterns, this paper proposes a unifying family of statistics, called TFisher, with general p-value truncation and weighting schemes. Analytical calculations for the p-value and the statistical power of TFisher under general hypotheses are given. Optimal truncation and weighting parameters are studied based on Bahadur Efficiency (BE) and the proposed Asymptotic Power Efficiency (APE), which is superior to BE for studying the signal detection problem. A soft-thresholding scheme is shown to be optimal for signal detection in a large space of signal patterns. When prior information of signal pattern is unavailable, an omnibus test, oTFisher, can adapt to the given data. Simulations evidenced the accuracy of calculations and validated the theoretical properties. The TFisher tests were applied to analyzing a whole exome sequencing data of amyotrophic lateral sclerosis. Relevant tests and calculations have been implemented into an R package TFisher and published on the CRAN. Copyright © 2018, The Authors. All rights reserved.

关键词： Signal detection

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VHP-Female full-body human CAD model for cross-platform FEM simulations — Recent development and validations

VHP-Female full-body human CAD model for cross-platform FEM ...

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Annual International Conference of the IEEE Engineering in Medicine and biology Society (EMBC)

作者： Harshal Tankaria Xavier J. Jackson Raunak Borwankar Goutham N. K. Srichandhru Anh Le Tran Janakinadh Yanamadala Gregory M. Noetscher Ara Nazarian Sara Louie Sergey N. Makarov Electrical and Computer Eng. Dept. Worcester Polytechnic Institute Worcester MA USA Bioinformatics and Computational Biology Dept. Worcester Polytechnic Institute Worcester MA USA NEVA Electromagnetics LLC MA USA Center for Advanced Orthopaedic Studies Harvard Med. School Boston MA ANSYS Inc. Canonsburg PA

关键词： computational modeling Solid modeling Electromagnetics Finite element analysis Phantoms Ribs Biological system modeling

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New VHP-Female v. 2.0 Full-Body computational Phantom and Its Performance Metrics Using FEM Simulator ANSYS HFSS

New VHP-Female v. 2.0 Full-Body Computational Phantom and It...

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Annual International Conference of the IEEE Engineering in Medicine and biology Society

作者： Janakinadh Yanamadala Gregory M. Noetscher Vishal K. Rathi Saili Maliye Htay A. Win Anh L. Tran Xavier J. Jackson Aung T. Htet Mikhail Kozlov Ara Nazarian Sara Louie Sergey N. Makarov the Electrical and Computer Eng. Dept. at Worcester Polytechnic Institute Worcester MA 01604 USA the Bioinformatics and Computational Biology Dept. at Worcester Polytechnic Institute Worcester MA 01604 USA the Department of Neurophysics at the Max Plank Inst. for Human Cognitive and Brain Sciences in Leipzig Germany the Center for Advanced Orthopaedic Studies at Beth Israel Deaconess Medical Center Harvard Med. School Boston MA ANSYS Inc. Canonsburg PA

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.

关键词： VHP Full-Body computational Phantom ANSYS HFSS

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Metabolic energy expenditure for time-varying isometric forces

arXiv

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arXiv 2024年

作者： Muralidhar, Sriram Sekaripuram Heitman, Kristen Walcott, Samuel C. Srinivasan, Manoj Mechanical and Aerospace Engineering The Ohio State University ColumbusOH43201 United States School of Health and Rehabilitation Sciences The Ohio State University ColumbusOH43201 United States Mathematical Sciences and Bioinformatics and Computational Biology Worcester Polytechnic Institute WorcesterMA01609 United States Program in Biophysics The Ohio State University ColumbusOH43201 United States

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 models developed so far have predominantly aimed at dynamic movement tasks, where me- chanical work dominates. Further, while it is known that both force magnitude and rate of change of force (force rate) affect metabolic cost, it is not known how these terms interact, or if the force rate dependence can be a consequence of the force dependence. Here, we performed extensive human subject experiments, involving each subject over 5 hours of metabolic trials, which systematically changed the mean forces and forces rates so as to characterize a holistic relation for metabolic cost based on both force and force rate - or analogously, torque and torque rate. Our experiments involved humans producing symmetric or asym- metric sinusoidal forces with different means, amplitudes, frequencies, and rise and fall periods. We showed that the metabolic cost can be well-approximated by a sum of power law functions of torque and torque rate. We found that the metabolic cost scales non-linearly with joint torque (with exponent 1 = 1.36) and non-linearly with torque rate (with exponent 2 = 2.5). Surprisingly, the data suggested that the cost was roughly four times higher for decreasing the torque than increasing, mirroring the analogous ratio between the cost of positive and negative work. Using these metabolic cost relations, we show that if the metabolic cost scales with particular exponents with muscle force and force rates, the same exponents will be observed in multi-joint tasks with multiple muscles. Our new metabolic cost model involving both force and force rate will potentially allow better predictions of energy optimal movements and thus inform wearable robot design and analysis. © 2024, CC BY.

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DOMMINO 2.0: Integrating structurally resolved protein-, RNA-, and DNA-mediated Macromolecular interactions

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Database 2016年第2016期2016卷 bav114页

作者： Kuang, Xingyan Dhroso, Andi Han, Jing Ginger Shyu, Chi-Ren Korkin, Dmitry Informatics Institute University of Missouri Columbia MO United States Department of Computer Science Bioinformatics and Computational Biology Program Worcester Polytechnic Institute Worcester MA United States Department of Electrical and Computer Engineering United States Department of Computer Science University of Missouri Columbia MO United States Ohio State University Comprehensive Cancer Center Columbus OH United States

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

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Evolution and Medicine: An Inquiry-Based High School Curriculum Supplement

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Evolution: Education and Outreach 2011年第4期4卷 603-612页

作者： Beardsley, Paul M. Stuhlsatz, Molly A.M. Kruse, Rebecca A. Eckstrand, Irene A. Gordon, Shefa D. Odenwald, Ward F. BSCS (Biological Sciences Curriculum Study) 5415 Mark Dabling Blvd Colorado Springs 80918 CO United States National Institute of General Medical Sciences Division of Genetics and Developmental Biology Center for Bioinformatics and Computational Biology 45 Center Drive Bethesda 20892-6200 MD United States National Eye Institute Office of Program Planning and Analysis 9000 Rockville Pike Bethesda 20892-6200 MD United States National Institute of Neurological Disorders and Stroke Neural Cell-Fate Determinants Section Bethesda 20892-6200 MD United States Center for Excellence in Mathematics and Science Teaching and Department of Biological Sciences CEMaST 4-2-515 California State Polytechnic University 3801 W. Temple Ave. Pomona 91768 CA United States

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 from NIH's Office of Science Education (OSE) as a part of the NIH curriculum supplement series. Development of the supplement was a collaborative effort that included input from a panel of experts in medicine, evolution, education, and educational technology. In total, the curriculum supplement includes five inquiry-based lessons that are integrated into the BSCS 5E instructional model (based on constructivist learning theory). The goal was to develop a 2-week curriculum to help students understand major concepts of evolution using the dynamic, modern, and relevant context of medicine. A diverse group of students and teachers across the US participated in a formative evaluation of a field test version of the curriculum. High school students made significant learning gains from pretest to posttest, with a relatively large effect size for student understanding of common ancestry and a relatively small effect size for student understanding of natural selection. There was no statistically significant difference in achievement gains between white students and all other racial/ethnic categories. Overall, the evaluation suggests that a curriculum that emphasizes the role of evolution in medicine, uses a constructivist instructional model, and is grounded in inquiry is relatively well-received by teachers and students and shows promise for increasing student learning in evolution. © 2011 Springer Science+Business Media, LLC.

关键词： Common ancestry Evolution Evolution and medicine High school Inquiry Instructional model Natural selection

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