Latest in q-bio.qm

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Musculoskeletal full-body models including a detailed thoracolumbar spine for children and adolescents aged 6 to 18 yearsJun 13 2019Currently available thoracolumbar spine models are entirely based on data from adults and might therefore not be applicable for simulations in children and adolescents. In addition, these models lack lower extremities, which are required for comprehensive ... More
Conditional Monte Carlo for Reaction NetworksJun 12 2019Reaction networks are often used to model interacting species in fields such as biochemistry and ecology. When the counts of the species are sufficiently large, the dynamics of their concentrations are typically modeled via a system of differential equations. ... More
A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical ApplicationsJun 12 2019We present a simple text mining method that is easy to implement, requires minimal data collection and preparation, and is easy to use for proposing ranked associations between a list of target terms and a key phrase. We call this method KinderMiner, ... More
Exploring Bayesian approaches to eQTL mapping through probabilistic programmingJun 12 2019The discovery of genomic polymorphisms influencing gene expression (also known as expression quantitative trait loci or eQTLs) can be formulated as a sparse Bayesian multivariate/multiple regression problem. An important aspect in the development of such ... More
Characterization and valuation of uncertainty of calibrated parameters in stochastic decision modelsJun 11 2019We evaluated the implications of different approaches to characterize uncertainty of calibrated parameters of stochastic decision models (DMs) in the quantified value of such uncertainty in decision making. We used a microsimulation DM of colorectal cancer ... More
Vaccination strategies to control Ebola epidemics in the context of variable household inaccessibility levelsJun 11 2019Despite a very effective vaccine, active conflict and community distrust during the ongoing DRC Ebola epidemic are undermining control efforts, including a ring vaccination strategy. However, 20% or more of close contacts cannot be reached or refused ... More
Automated generation of bacterial resource allocation modelsJun 11 2019Resource Balance Analysis (RBA) is a computational method based on resource allocation, which performs accurate quantitative predictions of whole-cell states (i.e. growth rate, meta-bolic fluxes, abundances of molecular machines including enzymes) across ... More
Multiscale Nakagami parametric imaging for improved liver tumor localizationJun 11 2019Effective ultrasound tissue characterization is usually hindered by complex tissue structures. The interlacing of speckle patterns complicates the correct estimation of backscatter distribution parameters. Nakagami parametric imaging based on localized ... More
Phylogenetic correlations can suffice to infer protein partners from sequencesJun 10 2019Determining which proteins interact together is crucial to a systems-level understanding of the cell. Recently, algorithms based on Direct Coupling Analysis (DCA) pairwise maximum-entropy models have allowed to identify interaction partners among the ... More
Multiparametric Deep Learning and Radiomics for Tumor Grading and Treatment Response Assessment of Brain Cancer: Preliminary ResultsJun 10 2019Radiomics is an exciting new area of texture research for extracting quantitative and morphological characteristics of pathological tissue. However, to date, only single images have been used for texture analysis. We have extended radiomic texture methods ... More
Parallel scalable simulations of biological neural networks using TensorFlow: A beginner's guideJun 10 2019Neuronal networks are often modeled as systems of coupled, nonlinear, ordinary or partial differential equations. The number of differential equations used to model a network increases with the size of the network and the level of detail used to model ... More
Integrative Factorization of Bidimensionally Linked MatricesJun 09 2019Advances in molecular "omics'" technologies have motivated new methodology for the integration of multiple sources of high-content biomedical data. However, most statistical methods for integrating multiple data matrices only consider data shared vertically ... More
Deep Contextualized Biomedical Abbreviation ExpansionJun 08 2019Automatic identification and expansion of ambiguous abbreviations are essential for biomedical natural language processing applications, such as information retrieval and question answering systems. In this paper, we present DEep Contextualized Biomedical. ... More
Cell image classification: a comparative overviewJun 07 2019Cell image classification methods are currently being used in numerous applications in cell biology and medicine. Applications include understanding the effects of genes and drugs in screening experiments, understanding the role and subcellular localization ... More
The first order statistics of backscatter from the fractal branching vasculatureJun 06 2019The issue of speckle statistics from ultrasound images of soft tissues such as the liver has a long and rich history. A number of theoretical distributions, some related to random scatterers or fades in optics and radar, have been formulated for pulse-echo ... More
The first order statistics of backscatter from the fractal branching vasculatureJun 06 2019Jun 07 2019The issue of speckle statistics from ultrasound images of soft tissues such as the liver has a long and rich history. A number of theoretical distributions, some related to random scatterers or fades in optics and radar, have been formulated for pulse-echo ... More
Unified framework for modeling multivariate distributions in biological sequencesJun 06 2019Revealing the functional sites of biological sequences, such as evolutionary conserved, structurally interacting or co-evolving protein sites, is a fundamental, and yet challenging task. Different frameworks and models were developed to approach this ... More
GIBBONR: An R package for the detection and classification of acoustic signals using machine learningJun 06 20191. The recent improvements in recording technology, data storage and battery life have led to an increased interest in the use of passive acoustic monitoring for a variety of research questions. One of the main obstacles in implementing wide scale acoustic ... More
A distribution-dependent analysis of open-field test moviesJun 04 2019Although the open-field test has been widely used, its reliability and compatibility are frequently questioned. Although many indicating parameters were introduced for this test, they did not take data distributions into consideration. This oversight ... More
Mathematical Discovery of Natural Laws in Biomedical Sciences: A New MethodologyJun 03 2019As biomedical sciences discover new layers of complexity in the mechanisms of life and disease, mathematical models trying to catch up with these developments become mathematically intractable. As a result, in the grand scheme of things, mathematical ... More
Bifurcation and CriticalityJun 03 2019Equilibrium and nonequilibrium systems exhibit power-law singularities close to their critical and bifurcation points respectively. A recent study has shown that biochemical nonequilibrium models with positive feedback belong to the universality class ... More
Loopy Lévy flights enhance tracer diffusion in active suspensionsJun 03 2019Brownian motion is widely used as a paradigmatic model of diffusion in equilibrium media throughout the physical, chemical, and biological sciences. However, many real world systems, particularly biological ones, are intrinsically out-of-equilibrium due ... More
Improved fragment-based movement with LRFragLib for all-atom Ab initio protein foldingJun 02 2019Fragment-based assembly has been widely used in Ab initio protein folding simulation which can effectively reduce the conformational space and thus accelerate sampling. The efficiency of fragment-based movement as well as the quality of fragment library ... More
MolecularRNN: Generating realistic molecular graphs with optimized propertiesMay 31 2019Designing new molecules with a set of predefined properties is a core problem in modern drug discovery and development. There is a growing need for de-novo design methods that would address this problem. We present MolecularRNN, the graph recurrent generative ... More
Custom Edge-Element FEM Solver and its Application to Eddy-Current Simulation of Realistic 2M-Element Human Brain PhantomMay 30 2019Extensive research papers of three-dimensional computational techniques are widely used for the investigation of human brain pathophysiology. Eddy current analyzing could provide an indication of conductivity change within a biological body. A significant ... More
Distinguishing states of conscious arousal using statistical complexityMay 30 2019We apply techniques from the field of computational mechanics to evaluate the statistical complexity of neural recording data in fruit flies. We connect statistical complexity to the flies' level of conscious arousal, which is manipulated by general anaesthesia ... More
Prostate Cancer Detection using Deep Convolutional Neural NetworksMay 30 2019Prostate cancer is one of the most common forms of cancer and the third leading cause of cancer death in North America. As an integrated part of computer-aided detection (CAD) tools, diffusion-weighted magnetic resonance imaging (DWI) has been intensively ... More
ImJoy: an open-source computational platform for the deep learning eraMay 30 2019Deep learning methods have shown extraordinary potential for analyzing very diverse biomedical data, but their dissemination beyond developers is hindered by important computational hurdles. We introduce ImJoy (https://imjoy.io/), a flexible and open-source ... More
Physically-Plausible Modelling of Biomolecular Systems: A Simplified, Energy-Based Model of the Mitochondrial Electron Transport ChainMay 30 2019Systems biology and whole-cell modelling are demanding increasingly comprehensive mathematical models of cellular biochemistry. These models require the development of simplified models of specific processes which capture essential biophysical features ... More
Leveraging binding-site structure for drug discovery with point-cloud methodsMay 28 2019Computational drug discovery strategies can be broadly placed in two categories: ligand-based methods which identify novel molecules by similarity with known ligands, and structure-based methods which predict molecules with high-affinity to a given 3D ... More
Collective-variable selection and generative Hopfield-Potts models for protein-sequence familiesMay 28 2019Statistical models for families of evolutionary related proteins have recently gained interest: in particular pairwise Potts models, as those inferred by the Direct-Coupling Analysis, have been able to extract information about the three-dimensional structure ... More
Persistent homology analysis of osmolyte molecular aggregation and their hydrogen-bonding networksMay 28 2019Two types of osmolytes, i.e., trimethylamin N-oxide (TMAO) and urea, demonstrate dramatically different properties in a protein folding process. Even with the great progresses in revealing the potential underlying mechanism of these two osmolyte systems, ... More
Real-time Cellular Impedance Monitoring and Imaging of Biological Barriers in a dual flow membrane bioreactorMay 27 2019The generation of physiologically relevant in-vitro models of biological barriers can play a key role in understanding human diseases and in the development of more predictive methods for assessing toxicity and drug or nutrient absorption. Here, we present ... More
The pH-dependent electrostatic interaction of a metal nanoparticle with the MS2 virus-like particlesMay 25 2019The electrostatic interaction of metal nanoparticles with viruses is attracting great interest due to their antiviral activity and their role in enhancing the detection of viruses at ultra-low concentrations. We model the MS2 virus devoid of its single ... More
Meshfree Methods on Manifolds for Hydrodynamic Flows on Curved Surfaces: A Generalized Moving Least-Squares (GMLS) ApproachMay 24 2019We utilize generalized moving least squares (GMLS) to develop meshfree techniques for discretizing hydrodynamic flow problems on manifolds. We use exterior calculus to formulate incompressible hydrodynamic equations in the Stokesian regime and handle ... More
Detection of Thalassaemia Carriers by Automated Feature Extraction of Dried Blood DropsMay 24 2019Thalassaemia, triggered by defects in the globin genes, is one of the most common monogenic diseases. The beta-thalassaemia carrier state is clinically asymptomatic, thus, making it onerous to diagnose. The current gold standard technique is implausible ... More
Improving Prognostic Value of CT Deep Radiomic Features in Pancreatic Ductal Adenocarcinoma Using Transfer LearningMay 23 2019Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers with an extremely poor prognosis. Radiomics has shown prognostic ability in multiple types of cancer including PDAC. However, the prognostic value of traditional radiomics pipelines, ... More
A COLD Approach to Generating Optimal SamplesMay 23 2019Optimising discrete data for a desired characteristic using gradient-based methods involves projecting the data into a continuous latent space and carrying out optimisation in this space. Carrying out global optimisation is difficult as optimisers are ... More
Exploring Diseases and Syndromes in Neurology Case Reports from 1955 to 2017 with Text MiningMay 23 2019Background: A large number of neurology case reports have been published, but it is a challenging task for human medical experts to explore all of these publications. Text mining offers a computational approach to investigate neurology literature and ... More
A model of brain morphological changes related to aging and Alzheimer's disease from cross-sectional assessmentsMay 23 2019In this study we propose a deformation-based framework to jointly model the influence of aging and Alzheimer's disease (AD) on the brain morphological evolution. Our approach combines a spatio-temporal description of both processes into a generative model. ... More
Selection of a Minimal Number of Significant Porcine SNPs by an Information Gain and Genetic Algorithm Hybrid ModelMay 22 2019A panel of large number of common Single Nucleotide Polymorphisms (SNPs) distributed across an entire porcine genome has been widely used to represent genetic variability of pig. With the advent of SNP-array technology, a genome-wide genetic profile of ... More
Dynamic Prediction of Competing Risk Events using Landmark Sub-distribution Hazard Model with Multiple Longitudinal BiomarkerMay 22 2019The cause-specific cumulative incidence function (CIF) quantifies the subject-specific disease risk with competing risk outcome. With longitudinally collected biomarker data, it is of interest to dynamically update the predicted CIF by incorporating the ... More
Molecular rules for selectivity in lipase-catalysed acylation of lysineMay 21 2019The selectivity of L-lysine acylation by lauric acid catalysed by Candida antarctica lipase B (CALB) was investigated combining experimental and theoretical methodologies. Experiments showed the near-exclusive acylation of lysine $\epsilon$-amino group; ... More
Tikhonov-Fenichel reduction for parameterized critical manifolds with applications to chemical reaction networksMay 20 2019We derive a reduction formula for singularly perturbed ordinary differential equations (in the sense of Tikhonov and Fenichel) with a known parameterization of the critical manifold. No a priori assumptions concerning separation of slow and fast variables ... More
Decoding the Rejuvenating Effects of Mechanical Loading on Skeletal Maturation using in Vivo Imaging and Deep LearningMay 20 2019Throughout the process of aging, deterioration of bone macro- and micro-architecture, as well as material decomposition result in a loss of strength and therefore in an increased likelihood of fractures. To date, precise contributions of age-related changes ... More
Magnetic resonance imaging of mean cell size in human breast tumorsMay 19 2019Purpose: Cell size is a fundamental characteristic of all tissues, and changes in cell size in cancer reflect tumor status and response to treatments, such as apoptosis and cell cycle arrest. Unfortunately, cell size can only be obtained by pathologic ... More
Quantification of the morphological characteristics of hESC coloniesMay 17 2019The maintenance of the pluripotent state in human embryonic stem cells (hESCs) is critical for further application in regenerative medicine, drug testing and studies of fundamental biology. Currently, the selection of the best quality cells and colonies ... More
Signal detection in extracellular neural ensemble recordings using higher criticismMay 15 2019Information processing in the brain is conducted by a concerted action of multiple neural populations. Gaining insights in the organization and dynamics of such populations can best be studied with broadband intracranial recordings of so-called extracellular ... More
From Brain Imaging to Graph Analysis: a study on ADNI's patient cohortMay 14 2019In this paper, we studied the association between the change of structural brain volumes to the potential development of Alzheimer's disease (AD). Using a simple abstraction technique, we converted regional cortical and subcortical volume differences ... More
Moment-Based Variational Inference for Markov Jump ProcessesMay 14 2019We propose moment-based variational inference as a flexible framework for approximate smoothing of latent Markov jump processes. The main ingredient of our approach is to partition the set of all transitions of the latent process into classes. This allows ... More
Using statistical techniques and replication samples for imputation of metabolite missing valuesMay 12 2019Background: Data preparation, such as missing values imputation and transformation, is the first step in any data analysis and requires crucial attention. Particularly, analysis of metabolites demands more preparation since those small compounds have ... More
Supervised machine learning based multi-task artificial intelligence classification of retinopathiesMay 10 2019Artificial intelligence (AI) classification holds promise as a novel and affordable screening tool for clinical management of ocular diseases. Rural and underserved areas, which suffer from lack of access to experienced ophthalmologists may particularly ... More
Digital System Reconstruction by Pairwise Transfer EntropyMay 10 2019Transfer entropy (TE) is an attractive model-free method to detect causality and infer structural connectivity of general digital systems. However it relies on high dimensions used in its definition to clearly remove the memory effect and distinguish ... More
Chaos in a continuous-time Boolean networkMay 09 2019Continuous-time systems with switch-like behaviour occur in chemical kinetics, gene regulatory networks and neural networks. Networks with hard switching, as a limiting case of smooth sigmoidal switching, retain the richest possible range of behaviors ... More
Tasks, Techniques, and Tools for Genomic Data VisualizationMay 08 2019Genomic data visualization is essential for interpretation and hypothesis generation as well as a valuable aid in communicating discoveries. Visual tools bridge the gap between algorithmic approaches and the cognitive skills of investigators. Addressing ... More
The Identification and Analysis of Indicators for Predicting Malarial Incidence in ZimbabweMay 07 2019With over 50% of the country's population at risk of contracting malaria despite the introduction of several measures to combat the disease, Zimbabwe is one of the eight countries in the Malaria Elimination 8 platform of the Southern African Development ... More
Deep phenotyping in C. elegansMay 07 2019Deep phenotyping study has become an emerging field to understand the gene function and the structure of biological networks. For the living animal C. elegans, recent advances in genome-editing tools, microfluidic devices and phenotypic analyses allow ... More
On the reorderability of node-filtered order complexesMay 07 2019Growing graphs describe a multitude of developing processes from maturing brains to expanding vocabularies to burgeoning public transit systems. Each of these growing processes likely adheres to proliferation rules that establish an effective order of ... More
Analysis of Gene Interaction Graphs for Biasing Machine Learning ModelsMay 06 2019Gene interaction graphs aim to capture various relationships between genes and can be used to create more biologically-intuitive models for machine learning. There are many such graphs available which can differ in the number of genes and edges covered. ... More
Machine Learning to Predict Developmental Neurotoxicity with High-throughput Data from 2D Bio-engineered TissuesMay 06 2019There is a growing need for fast and accurate methods for testing developmental neurotoxicity across several chemical exposure sources. Current approaches, such as in vivo animal studies, and assays of animal and human primary cell cultures, suffer from ... More
Mathematical Models of Gene ExpressionMay 06 2019In this paper we give an overview on the equilibrium properties of a large class of stochastic processes describing the fundamental biological process within cells, {\em the production process of proteins}. Stochastic models classically used in this context ... More
Mathematical Models of Gene ExpressionMay 06 2019May 13 2019In this paper we analyze the equilibrium properties of a large class of stochastic processes describing the fundamental biological process within bacterial cells, {\em the production process of proteins}. Stochastic models classically used in this context ... More
Moment-based analysis of biochemical feedback circuits in a population of chemically interacting cellsMay 06 2019Cells utilize chemical communication to exchange information and coordinate their behavior in noisy environments. Depending on the scenario, communication can reduce variability and shape a collective response, or amplify variability to generate distinct ... More
Estimating the Mutual Information between two Discrete, Asymmetric Variables with Limited SamplesMay 06 2019Determining the strength of non-linear statistical dependencies between two variables is a crucial matter in many research fields. The established measure for quantifying such relations is the mutual information. However, estimating mutual information ... More
Infant mortality across species. A global probe of congenital abnormalitiesMay 05 2019Infant mortality, by which we understand the postnatal stage during which mortality is declining, is a manifestation and embodiment of congenital abnormalities. Severe defects will translate into death occurring shortly after birth whereas slighter anomalies ... More
Congenital anomalies from a physics perspective. The key role of "manufacturing" volatilityMay 05 2019Genetic and environmental factors are traditionally seen as the sole causes of congenital anomalies. In this paper we introduce a third possible cause, namely random "manufacturing" discrepancies with respect to ``design'' values. A clear way to demonstrate ... More
Comparison About EEG Signals Processing in BCI ApplicationsMay 04 2019In the context of a Brain Computer Interface platform implemented for the arm rehabilitation of mildly impaired stroke patients, two methods of EEG signals processing are compared in terms of (i) their identification performance rate and (ii) their computational ... More
Renormalization group crossover in the critical dynamics of field theories with mode coupling termsMay 03 2019Motivated by the collective behaviour of biological swarms, we study the critical dynamics of field theories with coupling between order parameter and conjugate momentum in the presence of dissipation. By performing a dynamical renormalization group calculation ... More
Dynamical renormalization group approach to the collective behaviour of swarmsMay 03 2019We study the critical behaviour of a model with non-dissipative couplings aimed at describing the collective behaviour of natural swarms, using the dynamical renormalization group. At one loop, we find a crossover between a conservative yet unstable fixed ... More
Computational analysis of laminar structure of the human cortex based on local neuron featuresMay 03 2019In this paper, we present a novel method for analysis and segmentation of laminar structure of the cortex based on tissue characteristics whose change across the gray matter facilitates distinction between cortical layers. We develop and analyze features ... More
Multi-Scale Simulation Modeling for Prevention and Public Health Management of Diabetes in Pregnancy and SequelaeMay 03 2019Diabetes in pregnancy (DIP) is an increasing public health priority in the Australian Capital Territory, particularly due to its impact on risk for developing Type 2 diabetes. While earlier diagnostic screening results in greater capacity for early detection ... More
Control Variates for Stochastic Simulation of Chemical Reaction NetworksMay 02 2019Stochastic simulation is a widely used method for estimating quantities in models of chemical reaction networks where uncertainty plays a crucial role. However, reducing the statistical uncertainty of the corresponding estimators requires the generation ... More
Comprehensive classification of the plant non-specific lipid transfer protein superfamily towards its Sequence -Structure -Function analysisMay 02 2019Background. Non-specific Lipid Transfer Proteins (nsLTPs) are widely distributed in the plant kingdom and constitute a superfamily of related proteins. More than 800 different sequences have been characterized so far, but their biological functions remain ... More
Paper-based cell cryopreservationMay 02 2019The continuous development of simple and practical cell cryopreservation methods is of great importance to a variety of sectors, especially when considering the efficient short- and long-term storage of cells and their transportation. Although the overall ... More
Drug-Drug Adverse Effect Prediction with Graph Co-AttentionMay 02 2019Complex or co-existing diseases are commonly treated using drug combinations, which can lead to higher risk of adverse side effects. The detection of polypharmacy side effects is usually done in Phase IV clinical trials, but there are still plenty which ... More
Machine Learning for Classification of Protein Helix Capping MotifsMay 01 2019The biological function of a protein stems from its 3-dimensional structure, which is thermodynamically determined by the energetics of interatomic forces between its amino acid building blocks (the order of amino acids, known as the sequence, defines ... More
Theory of cyborg: a new approach to fish locomotion controlApr 29 2019Apr 30 2019Cyborg in the brain-machine interface field has attracted more attention in recent years. To control a creature via a machine called cyborg method, three stages are considerable: stimulation of neurons, neural response, and the behavioral reaction of ... More
Theory of cyborg: a new approach to fish locomotion controlApr 29 2019Cyborg in the brain-machine interface field has attracted more attention in recent years. To control a creature via a machine called cyborg method, three stages are considerable: stimulation of neurons, neural response, and the behavioral reaction of ... More
A new method of brain stimulation at ultra-high frequencyApr 29 2019Nerve stimulation via micro-electrode implants is one of the neurostimulation approaches which is used frequently in the medical treatment of some brain disorders, neural prosthetics, brain-machine interfaces and also in the cyborg. In this method, the ... More
TiCoNE 2: A Composite Clustering Model for Robust Cluster Analyses on Noisy DataApr 28 2019Identifying groups of similar objects using clustering approaches is one of the most frequently employed first steps in exploratory biomedical data analysis. Many clustering methods have been developed that pursue different strategies to identify the ... More
Temporal-Clustering Invariance in Irregular Healthcare Time SeriesApr 27 2019Electronic records contain sequences of events, some of which take place all at once in a single visit, and others that are dispersed over multiple visits, each with a different timestamp. We postulate that fine temporal detail, e.g., whether a series ... More
Time-dependent product-form Poisson distributions for reaction networks with higher order complexesApr 25 2019It is well known that stochastically modeled reaction networks that are complex balanced admit a stationary distribution that is a product of Poisson distributions. In this paper, we consider the following related question: supposing that the initial ... More
Towards Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-based Convolutional EncodersApr 25 2019In line with recent advances in neural drug design and sensitivity prediction, we propose a novel architecture for interpretable prediction of anticancer compound sensitivity using a multimodal attention-based convolutional encoder. Our model is based ... More
Towards Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-based Convolutional EncodersApr 25 2019May 22 2019In line with recent advances in neural drug design and sensitivity prediction, we propose a novel architecture for interpretable prediction of anticancer compound sensitivity using a multimodal attention-based convolutional encoder. Our model is based ... More
Coalescence in the diffusion limit of a Bienayme-Galton-Watson branching processApr 24 2019We consider the problem of estimating the elapsed time since the most recent common ancestor of a finite random sample drawn from a population which has evolved through a Bienayme-Galton-Watson branching process. More specifically, we are interested in ... More
Characterizing the nonlinear structure of shared variability in cortical neuron populations using latent variable modelsApr 23 2019Sensory neurons often have variable responses to repeated presentations of the same stimulus, which can significantly degrade the stimulus information contained in those responses. This information can in principle be preserved if variability is shared ... More
Radiogenomics models in precision radiotherapy: from mechanistic to machine learningApr 21 2019Machine learning provides a broad framework for addressing high-dimensional prediction problems in classification and regression. While machine learning is often applied for imaging problems in medical physics, there are many efforts to apply these principles ... More
Modelling Hierarchical FlockingApr 21 2019We present a general framework for modeling a wide selection of flocking scenarios under free boundary conditions. Several variants have been considered - including examples for the widely observed behavior of hierarchically interacting units. The models ... More
DeepMoD: Deep learning for Model Discovery in noisy dataApr 20 2019We introduce DeepMoD, a deep learning based model discovery algorithm which seeks the partial differential equation underlying a spatio-temporal data set. DeepMoD employs sparse regression on a library of basis functions and their corresponding spatial ... More
Don't be jelly: Exploring effective jellyfish locomotionApr 19 2019Jellyfish have been called one of the most energy-efficient animals in the world due to the ease in which they move through their fluid environment, by product of their morphological, muscular, and material properties. We investigated jellyfish locomotion ... More
A Framework for Predicting Impactability of Healthcare Interventions Using Machine Learning Methods, Administrative Claims, Sociodemographic and App Generated DataApr 19 2019It is not clear how to target patients who are most likely to benefit from digital care management programs ex-ante, a shortcoming of current risk score based approaches. This study focuses on defining impactability by identifying those patients most ... More
A Framework for Predicting Impactability of Healthcare Interventions Using Machine Learning Methods, Administrative Claims, Sociodemographic and App Generated DataApr 19 2019May 15 2019It is not clear how to target patients who are most likely to benefit from digital care management programs ex-ante, a shortcoming of current risk score based approaches. This study focuses on defining impactability by identifying those patients most ... More
Random Fragments Classification of Microbial Marker Clades with Multi-class SVM and N-Best AlgorithmApr 19 2019Microbial clades modeling is a challenging problem in biology based on microarray genome sequences, especially in new species gene isolates discovery and category. Marker family genome sequences play important roles in describing specific microbial clades ... More
Stochastically modeled weakly reversible reaction networks with a single linkage classApr 18 2019It has been known for nearly a decade that deterministically modeled reaction networks that are weakly reversible and consist of a single linkage class have bounded, persistent trajectories (i.e., for each trajectory $x(t)\in \R^d_{\ge 0}$, the expression ... More
Alterations in Structural Correlation Networks with Prior Concussion in Collision-Sport AthletesApr 18 2019Several studies have used structural correlation networks, derived from anatomical covariance of brain regions, to analyze neurologic changes associated with multiple sclerosis, schizophrenia and breast cancer [1][2]. Graph-theoretical analyses of human ... More
Hybrid Mortality Prediction using Multiple Source SystemsApr 18 2019The use of artificial intelligence in clinical care to improve decision support systems is increasing. This is not surprising since, by its very nature, the practice of medicine consists of making decisions based on observations from different systems ... More
Regulation of Heart Beats by the Autonomous Nervous System in Health and Disease: Point-Process-Theory based Models and Simulation [V-I]Apr 17 2019We have advanced a point-process based framework for the regulation of heart beats by the autonomous nervous system and analyzed the model with and without feedback. The model without feedback was found amenable to several analytical results that help ... More
Mathematical modeling of variability in intracellular signalingApr 17 2019Cellular signaling is essential in information processing and decision making. Therefore, a variety of experimental approaches have been developed to study signaling on bulk and single-cell level. Single-cell measurements of signaling molecules demonstrated ... More
A precise relationship among Buller's drop, ballistospore and gill morphology enables maximal packing of spores within gilled mushroomsApr 17 2019Basidiomycete fungi eject spores using a surface tension catapult; a fluid drop forms at the base of each spore and after reaching a critical size, coalesces with the spore and launches it from the gill surface. Although basidiomycetes function within ... More
Batched Stochastic Bayesian Optimization via Combinatorial Constraints DesignApr 17 2019In many high-throughput experimental design settings, such as those common in biochemical engineering, batched queries are more cost effective than one-by-one sequential queries. Furthermore, it is often not possible to directly choose items to query. ... More