Latest in q-bio.qm

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A mathematical model describing the localization and spread of influenza A virus infection within the human respiratory tractAug 22 2019Within the human respiratory tract (HRT), viruses diffuse through the periciliary fluid (PCF) bathing the epithelium, and travel upwards via advection towards the nose and mouth, as the mucus escalator entrains the PCF. While many mathematical models ... More
Diversity in Biology: definitions, quantification, and modelsAug 22 2019Diversity indices are useful single-number metrics for characterizing a complex distribution of a set of attributes across a population of interest. The utility of these different metrics or set of metrics depend on the context and application, and whether ... More
DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learningAug 20 2019Aug 21 2019The ultimate goal of drug design is to find novel compounds with desirable pharmacological properties. Designing molecules retaining particular scaffolds as the core structures of the molecules is one of the efficient ways to obtain potential drug candidates ... More
Issues arising from benchmarking single-cell RNA sequencing imputation methodsAug 19 2019On June 25th, 2018, Huang et al. published a computational method SAVER on Nature Methods for imputing dropout gene expression levels in single cell RNA sequencing (scRNA-seq) data. Huang et al. performed a set of comprehensive benchmarking analyses, ... More
CUDA optimized Neural Network predicts blood glucose control from quantified joint mobility and anthropometricsAug 19 2019Neural network training entails heavy computation with obvious bottlenecks. The Compute Unified Device Architecture (CUDA) programming model allows us to accelerate computation by passing the processing workload from the CPU to the graphics processing ... More
A Modified Ising Model of Barabási-Albert Network with Gene-type SpinsAug 19 2019The central question of systems biology is to understand how individual components of a biological system such as genes or proteins cooperate in emerging phenotypes resulting in the evolution of diseases. As living cells are open systems in quasi-steady ... More
Resolving challenges in deep learning-based analyses of histopathological images using explanation methodsAug 15 2019Deep learning has recently gained popularity in digital pathology due to its high prediction quality. However, the medical domain requires explanation and insight for a better understanding beyond standard quantitative performance evaluation. Recently, ... More
A minimum set of stable blocks for rational design of polypeptide chains Running head: A set of stable blocks for protein rational designAug 14 2019The aim of this work was to find a minimal set of structurally stable pentapeptides, which allows forming a polypeptide chain of a required 3D structure. To search for factors that ensure structural stability of the pentapeptide, we generated peptide ... More
Investigation of the impact of PTMs on the protein backbone conformationAug 14 2019Post-Translational Modifications (PTMs) are known to play a critical role in the regulation of the protein functions. Their impact on protein structures, and their link to disorder regions have already been spotted on the past decade. Nonetheless, the ... More
In silico prediction of protein flexibility with local structure approachAug 14 2019Flexibility is an intrinsic essential feature of protein structures, directly linked to their functions. To this day, most of the prediction methods use the crystallographic data (namely B-factors) as the only indicator of protein's inner flexibility ... More
Multilevel and multifidelity uncertainty quantification for cardiovascular hemodynamicsAug 13 2019Standard approaches for uncertainty quantification (UQ) in cardiovascular modeling pose challenges due to the large number of uncertain inputs and the significant computational cost of realistic 3D simulations. We propose an efficient UQ framework utilizing ... More
A physiological model of the inflammatory-thermal-pain-cardiovascular interactions during a pathogen challengeAug 13 2019Uncontrolled, excessive production of pro-inflammatory mediators from immune cells and traumatized tissues can cause systemic inflammatory issues like sepsis, one of the ten leading causes of death in the United States and one of the three leading causes ... More
Enabling Simulation of High-Dimensional Micro-Macro Biophysical Models through Hybrid CPU and Multi-GPU ParallelismAug 12 2019Micro-macro models provide a powerful tool to study the relationship between microscale mechanisms and emergent macroscopic behavior. However, the detailed microscopic modeling may require tracking and evolving a high-dimensional configuration space at ... More
Signaling gradients in surface dynamics as basis for planarian regenerationAug 12 2019Aug 13 2019We introduce and analyze a mathematical model for the regeneration of planarian flatworms. This system of differential equations incorporates dynamics of head and tail cells which express positional control genes that in turn translate into localized ... More
Signaling gradients in surface dynamics as basis for planarian regenerationAug 12 2019We introduce and analyze a mathematical model for the regeneration of planarian flatworms. This system of differential equations incorporates dynamics of head and tail cells which express positional control genes that in turn translate into localized ... More
A new Granger causality measure for eliminating the confounding influence of latent common inputsAug 11 2019In this paper, we propose a new Granger causality measure which is robust against the confounding influence of latent common inputs. This measure is inspired by partial Granger causality in the literature, and its variant. Using numerical experiments ... More
Identification of relevant diffusion MRI metrics impacting cognitive functions using a novel feature selection methodAug 10 2019Mild Traumatic Brain Injury (mTBI) is a significant public health problem. The most troubling symptoms after mTBI are cognitive complaints. Studies show measurable differences between patients with mTBI and healthy controls with respect to tissue microstructure ... More
The role of cue enhancement and frequency fine-tuning in hearing impaired phone recognitionAug 09 2019A speech-based hearing test is designed to identify the susceptible error-prone phones for individual hearing impaired (HI) ear. Only robust tokens in the experiment noise levels had been chosen for the test. The noise-robustness of tokens is measured ... More
SERS discrimination of single amino acid residue in single peptide by plasmonic nanocavitiesAug 09 2019Surface-enhanced Raman spectroscopy (SERS) is a sensitive label-free optical method that can provide fingerprint Raman spectra of biomolecules such as DNA, amino acids and proteins. While SERS of single DNA molecule has been recently demonstrated, Raman ... More
A practical guide to methodological considerations in the controllability of structural brain networksAug 09 2019Predicting how the brain can be driven to specific states by means of internal or external control requires a fundamental understanding of the relationship between neural connectivity and activity. Network control theory is a powerful tool from the physical ... More
Naut your everyday jellyfish model: Exploring how tentacles and oral arms impact locomotionAug 09 2019Jellyfish - majestic, energy efficient, and one of the oldest species that inhabits the oceans. It is perhaps the second item, their efficiency, that has captivated scientists for decades into investigating their locomotive behavior. Yet, no one has specifically ... More
The Channel Attention based Context Encoder Network for Inner Limiting Membrane DetectionAug 09 2019The optic disc segmentation is an important step for retinal image-based disease diagnosis such as glaucoma. The inner limiting membrane (ILM) is the first boundary in the OCT, which can help to extract the retinal pigment epithelium (RPE) through gradient ... More
Concepts and Applications of Conformal Prediction in Computational Drug DiscoveryAug 09 2019Estimating the reliability of individual predictions is key to increase the adoption of computational models and artificial intelligence in preclinical drug discovery, as well as to foster its application to guide decision making in clinical settings. ... More
Deep Learning for Visual Recognition of Environmental Enteropathy and Celiac DiseaseAug 08 2019Physicians use biopsies to distinguish between different but histologically similar enteropathies. The range of syndromes and pathologies that could cause different gastrointestinal conditions makes this a difficult problem. Recently, deep learning has ... More
Identification of Effective Connectivity SubregionsAug 08 2019Standard fMRI connectivity analyses depend on aggregating the time series of individual voxels within regions of interest (ROIs). In certain cases, this spatial aggregation implies a loss of valuable functional and anatomical information about smaller ... More
AxoNet: an AI-based tool to count retinal ganglion cell axonsAug 08 2019Goal: In this work, we develop a robust, extensible tool to automatically and accurately count retinal ganglion cell axons in images of optic nerve tissue from various animal models of glaucoma. Methods: The U-Net convolutional neural network architecture ... More
Predicted disease compositions of human gliomas estimated from multiparametric MRI can predict endothelial proliferation, tumor grade, and overall survivalAug 06 2019Background and Purpose: Biopsy is the main determinants of glioma clinical management, but require invasive sampling that fail to detect relevant features because of tumor heterogeneity. The purpose of this study was to evaluate the accuracy of a voxel-wise, ... More
Characterizing the limits of human stability during motion: perturbative experiment validates a model-based approach for the Sit-to-Stand taskAug 05 2019Falls affect a growing number of the population each year. Clinical methods to identify those at greatest risk for falls usually evaluate individuals while they perform specific motions such as balancing or Sit-to-Stand (STS). Unfortunately these techniques ... More
Unsupervised Representations of Pollen in Bright-Field MicroscopyAug 05 2019We present the first unsupervised deep learning method for pollen analysis using bright-field microscopy. Using a modest dataset of 650 images of pollen grains collected from honey, we achieve family level identification of pollen. We embed images of ... More
High Accuracy Tumor Diagnoses and Benchmarking of Hematoxylin and Eosin Stained Prostate Core Biopsy Images Generated by Explainable Deep Neural NetworksAug 02 2019Histopathological diagnoses of tumors in tissue biopsy after Hematoxylin and Eosin (H&E) staining is the gold standard for oncology care. H&E staining is slow and uses dyes, reagents and precious tissue samples that cannot be reused. Thousands of native ... More
Random-effects meta-analysis of phase I dose-finding studies using stochastic process priorsAug 01 2019Phase I dose-finding studies aim at identifying the maximal tolerated dose (MTD). It is not uncommon that several dose-finding studies are conducted, although often with some variation in the administration mode or dose panel. For instance, sorafenib ... More
Climate-driven statistical models as effective predictors of local dengue incidence in Costa Rica: A Generalized Additive Model and Random Forest approachJul 30 2019Climate has been an important factor in shaping the distribution and incidence of dengue cases in tropical and subtropical countries. In Costa Rica, a tropical country with distinctive micro-climates, dengue has been endemic since its introduction in ... More
Two channel compartmentalized microfluidic chip for real time monitoring of the metastatic cascadeJul 30 2019Metastases are the primary cause of death in cancer patients. Small animal models are helping in dissecting some of key features in the metastatic cascade. Yet, tools for systematically analyze the contribution of blood flow, vascular permeability, inflammation, ... More
Development of a Fragment-Based Machine Learning Algorithm for Designing Hybrid Drugs Optimized for Permeating Gram-Negative BacteriaJul 29 2019Gram-negative bacteria are a serious health concern due to the strong multidrug resistance that they display, partly due to the presence of a permeability barrier comprising two membranes with active efflux. New approaches are urgently needed to design ... More
Uniform intensity in multifocal microscopy using a spatial light modulatorJul 29 2019Multifocal microscopy (MFM) offers high-speed three-dimensional imaging through the simultaneous image capture from multiple focal planes. Conventional MFM systems use a fabricated grating in the emission path for a single emission wavelength band and ... More
Discovering Association with Copula EntropyJul 29 2019Discovering associations is of central importance in scientific practices. Currently, most researches consider only linear association measured by correlation coefficient, which has its theoretical limitations. In this paper, we propose a new method for ... More
Calculating Germinal Centre ReactionsJul 28 2019Germinal centres are anatomically defined lymphoid organ structures that mediate B cell affinity maturation and affect the quality of humoral immune responses. Mathematical models based on differential equations or agent-based simulations have been widely ... More
A Matrix--free Likelihood Method for Exploratory Factor Analysis of High-dimensional Gaussian DataJul 27 2019This paper proposes a novel profile likelihood method for estimating the covariance parameters in exploratory factor analysis of high-dimensional Gaussian datasets with fewer observations than number of variables. An implicitly restarted Lanczos algorithm ... More
Deep learning-based prediction of kinetic parameters from myocardial perfusion MRIJul 27 2019The quantification of myocardial perfusion MRI has the potential to provide a fast, automated and user-independent assessment of myocardial ischaemia. However, due to the relatively high noise level and low temporal resolution of the acquired data and ... More
Molecular Brightness analysis of GPCR oligomerization in the presence of spatial heterogeneityJul 25 2019Measuring the oligomerization of plasma membrane proteins is rife with biophysical and biomedical implications. This is particularly true for GPCRs, a large family of proteins representing the targets of over one third of all FDA approved medications. ... More
Persistent exclusion processes: inertia, drift, mixing and correlationJul 25 2019In many biological systems, motile agents exhibit random motion with short-term directional persistence, together with crowding effects arising from spatial exclusion. We formulate and study a class of lattice-based models for multiple walkers with motion ... More
A nonconvex optimization approach to IMRT planning with dose-volume constraintsJul 24 2019Fluence map optimization for intensity-modulated radiation therapy planning can be formulated as a large-scale inverse problem with multi-objectives on the tumors and organs-at-risk. Unfortunately, clinically relevant dose-volume constraints are nonconvex, ... More
Gait recognition via deep learning of the center-of-pressure trajectoryJul 24 2019Analyzing the force that a walking individual applies to the ground has been proposed for identification purpose. Using end-to-end learning, I investigated whether the center-of-pressure trajectory is sufficiently unique to identify a person with a high ... More
Inferring long-range interactions between immune and tumor cells -- pitfalls and (partial) solutionsJul 24 2019Upcoming immunotherapies for cancer treatment rely on the ability of the immune system to detect and eliminate tumors in the body. A highly simplified version of this process can be studied in a Petri dish: starting with a random distribution of immune ... More
Movement science needs different pose tracking algorithmsJul 24 2019Over the last decade, computer science has made progress towards extracting body pose from single camera photographs or videos. This promises to enable movement science to detect disease, quantify movement performance, and take the science out of the ... More
Temporal connection signatures of human brain networks after strokeJul 23 2019Plasticity after stroke is a complex phenomenon initiated by the functional reorganization of the brain, especially in the perilesional tissue. At macroscales, the reestablishment of segregation within the affected hemisphere and interhemispheric integration ... More
Combinatorial protein-protein interactions on a polymerizing scaffoldJul 23 2019Scaffold proteins organize cellular processes by bringing signaling molecules into interaction, sometimes by forming large signalosomes. Several of these scaffolds are known to polymerize. Their assemblies should therefore not be understood as stoichiometric ... More
Robust Nuclei Detection from Microscopical Image with Partially Labeled ExemplarsJul 23 2019Quantitative analyses of cells' nuclei in microscopical images is an essential yet still challenging step for further biological and pathological information. Accurate detection and segmentation of densely-packed nuclei in images acquired under a variety ... More
Predicting Clinical Outcome of Stroke Patients with Tractographic FeatureJul 22 2019The volume of stroke lesion is the gold standard for predicting the clinical outcome of stroke patients. However, the presence of stroke lesion may cause neural disruptions to other brain regions, and these potentially damaged regions may affect the clinical ... More
Spatial patterns emerging from a stochastic process near criticalityJul 20 2019There is mounting empirical evidence that many communities of living organisms display key features which closely resemble those of physical systems at criticality. We here introduce a minimal model framework for the dynamics of a community of individuals ... More
Topological Methods for Characterising Spatial Networks: A Case Study in Tumour VasculatureJul 19 2019Understanding how the spatial structure of blood vessel networks relates to their function in healthy and abnormal biological tissues could improve diagnosis and treatment for diseases such as cancer. New imaging techniques can generate multiple, high-resolution ... More
Topology and geometry of molecular conformational spaces and energy landscapesJul 18 2019Understanding the geometry and topology of configuration or conformational spaces of molecules has relevant applications in chemistry and biology such as the proteins folding problem, drug design and the structure activity relationship problem. Despite ... More
Parameter estimation for biochemical reaction networks using Wasserstein distancesJul 18 2019We present a method for estimating parameters in stochastic models of biochemical reaction networks by fitting steady-state distributions using Wasserstein distances. We simulate a reaction network at different parameter settings and train a Gaussian ... More
An AI-Augmented Lesion Detection Framework For Liver Metastases With Model InterpretabilityJul 17 2019Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer-related deaths worldwide. Most CRC deaths are the result of progression of metastases. The assessment of metastases is done using the RECIST criterion, which ... More
A probabilistic approach to extreme statistics of Brownian escape times in dimensions 1, 2, and 3Jul 17 2019First passage time (FPT) theory is often used to estimate timescales in cellular and molecular biology. While the overwhelming majority of studies have focused on the time it takes a given single Brownian searcher to reach a target, cellular processes ... More
Improving Outbreak Detection with Stacking of Statistical Surveillance MethodsJul 17 2019Epidemiologists use a variety of statistical algorithms for the early detection of outbreaks. The practical usefulness of such methods highly depends on the trade-off between the detection rate of outbreaks and the chances of raising a false alarm. Recent ... More
Motzkin path on RNA abstract shapesJul 17 2019We consider a certain abstract of RNA secondary structures, which is closely related to RNA shapes. The generating function counting the number of the abstract structures is obtained by means of Narayana numbers and 2-Motzkin paths, through which we provide ... More
Spectral Cross-Cumulants for Multicolor Super-resolved SOFI ImagingJul 16 2019Super-resolution optical fluctuation imaging (SOFI) provides a resolution beyond the diffraction limit by analysing stochastic fluorescence fluctuations with higher-order statistics. Using nth order spatio-temporal cross-cumulants the spatial resolution ... More
Evaluating the Reproducibility of Research in Obstetrics and GynecologyJul 16 2019Objective: Reproducibility is a core tenet of scientific research. A reproducible study is one where the results can be recreated by different investigators in different circumstances using the same methodology and materials. Unfortunately, reproducibility ... More
Extensible and Scalable Adaptive Sampling on SupercomputersJul 16 2019The accurate sampling of protein dynamics is an ongoing challenge despite the utilization of High-Performance Computers (HPC) systems. Utilizing only "brute force" MD simulations requires an unacceptably long time to solution. Adaptive sampling methods ... More
Modulation in background music influences sustained attentionJul 16 2019Background music is known to affect performance on cognitive tasks, possibly due to temporal modulations in the acoustic signal, but little is known about how music should be designed to aid performance. Since acoustic modulation has been shown to shape ... More
Image-Driven Biophysical Tumor Growth Model CalibrationJul 16 2019We present a novel formulation for the calibration of a biophysical tumor growth model from a single-time snapshot, MRI scan of a glioblastoma patient. Tumor growth models are typically nonlinear parabolic partial differential equations (PDEs). Thus, ... More
Deciphering Dynamical Nonlinearities in Short Time Series Using Recurrent Neural NetworksJul 15 2019Surrogate testing techniques have been used widely to investigate the presence of dynamical nonlinearities, an essential ingredient of deterministic chaotic processes. Traditional surrogate testing subscribes to statistical hypothesis testing and investigates ... More
MOD-Finder: Identify multi-omics data sets related to defined chemical exposureJul 15 2019Summary: Integration of multi-omics data on chemical exposure of cells or organisms promises a more complete representation of the responding pathways than single omics data. Data of different omics layers, like transcriptome or proteome is deposited ... More
Weighted persistent homology for osmolyte molecular aggregation and hydrogen-bonding network analysisJul 14 2019It has long been observed that trimethylamin N-oxide (TMAO) and urea demonstrate dramatically different properties in a protein folding process. Even with the enormous theoretical and experimental research work of the two osmolytes, various aspects of ... More
Cortical Surface Parcellation using Spherical Convolutional Neural NetworksJul 11 2019We present cortical surface parcellation using spherical deep convolutional neural networks. Traditional multi-atlas cortical surface parcellation requires inter-subject surface registration using geometric features with high processing time on a single ... More
Warfarin dose estimation on multiple datasets with automated hyperparameter optimisation and a novel software frameworkJul 11 2019Warfarin is an effective preventative treatment for arterial and venous thromboembolism, but requires individualised dosing due to its narrow therapeutic range and high individual variation. A plethora of statistical and machine learning techniques have ... More
Distribution of outbreak sizes for SIR disease in finite populationsJul 11 2019We consider the spread of a Susceptible-Infected-Recovered (SIR) disease through finite populations and derive an expression for the final size distribution. Our derivation allows arbitrary distributions of the number of transmissions caused by an infected ... More
FindeR: Accelerating FM-Index-based Exact Pattern Matching in Genomic Sequences through ReRAM technologyJul 11 2019Genomics is the critical key to enable the precision medicine, ensure the global food security and enforce the wildlife conservation. The massive genomic data produced by various genome sequencing technologies presents a significant challenge for genome ... More
Application of a pixel color- and coordinate-based K-means clustering algorithm and RGB color imaging for quantification of rice sheath blight infectionJul 10 2019Red-green-blue (RGB) digital image-based detection is a promising alternative approach to the existing subjectivity-prone and labor-intensive plant disease quantification methods. K-means clustering (KMC) is a widely used algorithm for processing plant ... More
Improving Prognostic Performance in Resectable Pancreatic Ductal Adenocarcinoma using Radiomics and Deep Learning Features Fusion in CT ImagesJul 10 2019As an analytic pipeline for quantitative imaging feature extraction and analysis, radiomics has grown rapidly in the past a few years. Recent studies in radiomics aim to investigate the relationship between tumors imaging features and clinical outcomes. ... More
Coarse Graining of Data via Inhomogeneous Diffusion CondensationJul 10 2019Big data often has emergent structure that exists at multiple levels of abstraction, which are useful for characterizing complex interactions and dynamics of the observations. Here, we consider multiple levels of abstraction via a multiresolution geometry ... More
Deep Learning Techniques for Improving Digital Gait SegmentationJul 09 2019Wearable technology for the automatic detection of gait events has recently gained growing interest, enabling advanced analyses that were previously limited to specialist centres and equipment (e.g., instrumented walkway). In this study, we present a ... More
Applications of a Novel Knowledge Discovery and Data Mining Process Model for MetabolomicsJul 09 2019Jul 30 2019This work demonstrates the execution of a novel process model for knowledge discovery and data mining for metabolomics (MeKDDaM). It aims to illustrate MeKDDaM process model applicability using four different real-world applications and to highlight its ... More
Applications of a Novel Knowledge Discovery and Data Mining Process Model for MetabolomicsJul 09 2019This work demonstrates the execution of a novel process model for knowledge discovery and data mining for metabolomics (MeKDDaM). It aims to illustrate MeKDDaM process model applicability using four different real-world applications and to highlight its ... More
Computer-Aided Data Mining: Automating a Novel Knowledge Discovery and Data Mining Process Model for MetabolomicsJul 09 2019This work presents MeKDDaM-SAGA, computer-aided automation software for implementing a novel knowledge discovery and data mining process model that was designed for performing justifiable, traceable and reproducible metabolomics data analysis. The process ... More
Quantitative Immunology for PhysicistsJul 08 2019The adaptive immune system is a dynamical, self-organized multiscale system that protects vertebrates from both pathogens and internal irregularities, such as tumours. For these reason it fascinates physicists, yet the multitude of different cells, molecules ... More
Quantitative Immunology for PhysicistsJul 08 2019Jul 28 2019The adaptive immune system is a dynamical, self-organized multiscale system that protects vertebrates from both pathogens and internal irregularities, such as tumours. For these reason it fascinates physicists, yet the multitude of different cells, molecules ... More
False Discovery Rates in Biological NetworksJul 08 2019The increasing availability of data has generated unprecedented prospects for network analyses in many biological fields, such as neuroscience (e.g., brain networks), genomics (e.g., gene-gene interaction networks), and ecology (e.g., species interaction ... More
Aggregated False Discovery Rate ControlJul 08 2019We propose an aggregation scheme for methods that control the false discovery rate (FDR). Our scheme retains the underlying methods' FDR guarantees in theory and can decrease FDR and increase power in practice.
Numerical Optimization of Plasmid DNA Delivery Combined with Hyaluronidase Injection for Electroporation ProtocolJul 08 2019The definition of an innovative therapeutic protocol requires the fine tuning of all the involved operations in order to maximize the efficiency. In some cases, the price of the experiments, or their duration, represents a great obstacle and the full ... More
High-Throughput Machine Learning from Electronic Health RecordsJul 03 2019The widespread digitization of patient data via electronic health records (EHRs) has created an unprecedented opportunity to use machine learning algorithms to better predict disease risk at the patient level. Although predictive models have previously ... More
Cavopulmonary Support Operating Criteria for Serving the Failing Fontan Population; A Modeling InvestigatingJul 02 2019Fontan operation as the current ultimate palliation of single ventricle defects results in significant late complications eventually leading to a failing circulation. It has been suggested that introducing a cavopulmonary assist device to serve the function ... More
Molecular activity prediction using graph convolutional deep neural network considering distance on a molecular graphJul 02 2019Machine learning is often used in virtual screening to find compounds that are pharmacologically active on a target protein. The weave module is a type of graph convolutional deep neural network that uses not only features focusing on atoms alone (atom ... More
Molecular activity prediction using graph convolutional deep neural network considering distance on a molecular graphJul 02 2019Jul 04 2019Machine learning is often used in virtual screening to find compounds that are pharmacologically active on a target protein. The weave module is a type of graph convolutional deep neural network that uses not only features focusing on atoms alone (atom ... More
Neural parameters estimation for brain tumor growth modelingJul 01 2019Understanding the dynamics of brain tumor progression is essential for optimal treatment planning. Cast in a mathematical formulation, it is typically viewed as evaluation of a system of partial differential equations, wherein the physiological processes ... More
Estimating brain age based on a healthy population with deep learning and structural MRIJul 01 2019Numerous studies have established that estimated brain age, as derived from statistical models trained on healthy populations, constitutes a valuable biomarker that is predictive of cognitive decline and various neurological diseases. In this work, we ... More
Estimating Treatment Effect under Additive Hazards Models with High-dimensional CovariatesJun 29 2019Estimating causal effects for survival outcomes in the high-dimensional setting is an extremely important topic for many biomedical applications as well as areas of social sciences. We propose a new orthogonal score method for treatment effect estimation ... More
Second-generation stoichiometric mathematical model to predict methane emissions from oil sands tailingsJun 29 2019Microbial metabolism of fugitive hydrocarbons produces greenhouse gas (GHG) emissions from oil sands tailings ponds (OSTP) and end pit lakes (EPL) that retain semisolid wastes from surface mining of oil sands ores. Predicting GHG production, particularly ... More
Cellular State Transformations using Generative Adversarial NetworksJun 28 2019We introduce a novel method to unite deep learning with biology by which generative adversarial networks (GANs) generate transcriptome perturbations and reveal condition-defining gene expression patterns. We find that a generator conditioned to perturb ... More
Parallel Performance of Molecular Dynamics Trajectory AnalysisJun 28 2019The performance of biomolecular molecular dynamics (MD) simulations has steadily increased on modern high performance computing (HPC) resources but acceleration of the analysis of the output trajectories has lagged behind so that analyzing simulations ... More
A multifactorial evaluation framework for gene regulatory network reconstructionJun 28 2019In the past years, many computational methods have been developed to infer the structure of gene regulatory networks from time-series data. However, the applicability and accuracy presumptions of such algorithms remain unclear due to experimental heterogeneity. ... More
Structure and dynamics of dynorphin peptide and its receptorJun 27 2019Dynorphin is a neuropeptide involved in pain, addiction and mood regulation. It exerts its activity by binding to the kappa opioid receptor (KOP) which belongs to the large family of G-protein coupled receptors. The dynorphin peptide was discovered in ... More
Lattice Boltzmann method for simulation of diffusion magnetic resonance imaging physics in heterogeneous tissue modelsJun 26 2019We report the first implementation of the Lattice Boltzmann method (LBM) to integrate the Bloch-Torrey equation, which describes the evolution of the transverse magnetization vector and the fate of the signal of diffusion magnetic resonance imaging (dMRI). ... More
Parameter Estimation and Uncertainty Quantification for Systems Biology ModelsJun 26 2019Mathematical models can provide quantitative insight into immunoreceptor signaling, but require parameterization and uncertainty quantification before making reliable predictions. We review currently available methods and software tools to address these ... More
Multidimensional Contrast Limited Adaptive Histogram EqualizationJun 26 2019Jul 17 2019Contrast enhancement is an important preprocessing technique for improving the performance of downstream tasks in image processing and computer vision. Among the existing approaches based on nonlinear histogram transformations, contrast limited adaptive ... More
Multidimensional Contrast Limited Adaptive Histogram EqualizationJun 26 2019Contrast enhancement is an important preprocessing technique for improving the performance of downstream tasks in image processing and computer vision. Among the existing approaches based on nonlinear histogram transformations, contrast limited adaptive ... More
Generalized Median Graph via Iterative Alternate MinimizationsJun 26 2019Computing a graph prototype may constitute a core element for clustering or classification tasks. However, its computation is an NP-Hard problem, even for simple classes of graphs. In this paper, we propose an efficient approach based on block coordinate ... More
CNN-based Survival Model for Pancreatic Ductal Adenocarcinoma in Medical ImagingJun 25 2019Cox proportional hazard model (CPH) is commonly used in clinical research for survival analysis. In quantitative medical imaging (radiomics) studies, CPH plays an important role in feature reduction and modeling. However, the underlying linear assumption ... More
Survey of Information Encoding Techniques for DNAJun 24 2019Key to DNA storage is encoding the information to a sequence of nucleotides before it can be synthesised for storage. Definition of such an encoding or mapping must adhere to multiple design restrictions. First, not all possible sequences of nucleotides ... More