Latest in q-bio.qm

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Linear system identification from ensemble snapshot observationsMar 15 2019Developments in transcriptomics techniques have caused a large demand in tailored computational methods for modelling gene expression dynamics from experimental data. Recently, so-called single-cell experiments have revolutionised genetic studies. These ... More
AptaBlocks Online - A web-based toolkit for the in-silico assembly of RNA complexesMar 13 2019Summary: The AptaBlocks Web Interface is focused on providing graphical, intuitive, and platform independent access to AptaBlocks, an experimentally validated algorithmic approach for the in-silico design of oligonucleotide sticky bridges. The availability ... More
Climbing Escher's stairs: a simple quasi-potential algorithm for weakly non-gradient systemsMar 13 2019Stability landscapes are useful tools for understanding dynamical systems. These landscapes are usually calculated from differential equations in analogy with the physical concept of scalar potential. Unfortunately, the conditions for those potentials ... More
Span observables - "When is a foraging rabbit no longer hungry?"Mar 13 2019Be $X_t$ a random walk. We study its span $S$, i.e. the size of the domain visited up to time $t$. We want to know the probability that $S$ reaches $1$ for the first time, as well as the density of the span given $t$. Analytical results are presented, ... More
Who and When to Screen: Multi-Round Active Screening for Recurrent Infectious Diseases Under UncertaintyMar 13 2019Controlling recurrent infectious diseases is a vital yet complicated problem. In this paper, we propose a novel active screening model (ACTS) and algorithms to facilitate active screening for recurrent diseases (no permanent immunity) under infection ... More
Ribosome flow model with different site sizesMar 12 2019We introduce and analyze two general dynamical models for unidirectional movement of particles along a circular chain and an open chain of sites. The models include a soft version of the simple exclusion principle, that is, as the density in a site increases ... More
Identifying branching principles in biological networks using imaging, modeling, and machine learningMar 11 2019Branching in vascular networks and in overall organismic form is one of the most common and ancient features of multicellular plants, fungi and animals. These networks deliver resources and eliminate wastes from early development onward, and even play ... More
Detecting drug-drug interactions using artificial neural networks and classic graph similarity measuresMar 11 2019Drug-drug interactions are preventable causes of medical injuries and often result in doctor and emergency room visits. Computational techniques can be used to predict potential drug-drug interactions. We approach the drug-drug interaction prediction ... More
Better-than-expert detection of early coronary artery occlusion from 12 lead electrocardiograms using deep learningMar 11 2019Mar 13 2019Early diagnosis of acute coronary artery occlusion based on electrocardiogram (ECG) findings is essential for prompt delivery of primary percutaneous coronary intervention. Current ST elevation (STE) criteria are specific but insensitive. Consequently, ... More
Better-than-expert detection of early coronary artery occlusion from 12 lead electrocardiograms using deep learningMar 11 2019Early diagnosis of acute coronary artery occlusion based on electrocardiogram (ECG) findings is essential for prompt delivery of primary percutaneous coronary intervention. Current ST elevation (STE) criteria are specific but insensitive. Consequently, ... More
Using satellite image classification and digital terrain modelling to assess forest species distribution on mountain slopes.A case study in Varatec Forest DistrictMar 11 2019The relation between ecological conditions and geomorphological factors is considered the basis for species distribution in Romania. In this context, the location of each species within parts of the mountain slopes is difficult on a medium to brad scale ... More
Event-Based Modeling with High-Dimensional Imaging Biomarkers for Estimating Spatial Progression of DementiaMar 08 2019Event-based models (EBM) are a class of disease progression models that can be used to estimate temporal ordering of neuropathological changes from cross-sectional data. Current EBMs only handle scalar biomarkers, such as regional volumes, as inputs. ... More
Hierarchical microplates as drug depots with controlled geometry, rigidity and therapeutic efficacyMar 08 2019A variety of microparticles have been proposed for the sustained and localized delivery of drugs whit the objective of increasing therapeutic indexes by circumventing filtering organs and biological barriers. Yet, the geometrical, mechanical and therapeutic ... More
Robust Inference of Forces in Heterogeneous EnvironmentsMar 07 2019We devise a method to obtain a robust estimate of forces in a heterogeneous environment based on experimentally recorded trajectories. In particular, we focus on systems modeled by the heterogeneous overdamped Langevin equation. Here, the observed force ... More
Interpretable Deep Learning in Drug DiscoveryMar 07 2019Without any means of interpretation, neural networks that predict molecular properties and bioactivities are merely black boxes. We will unravel these black boxes and will demonstrate approaches to understand the learned representations which are hidden ... More
Collective movement in alarmed animals groups: a simple model with positional forces and a limited attention fieldMar 06 2019We perform a numerical analysis of a recent introduced model for describing collective movement in alarmed animals groups. This model, derived from a position-based interaction and a limited attention field, displays a non-equilibrium phase transition ... More
SleepEEGNet: Automated Sleep Stage Scoring with Sequence to Sequence Deep Learning ApproachMar 05 2019Electroencephalogram (EEG) is a common base signal used to monitor brain activity and diagnose sleep disorders. Manual sleep stage scoring is a time-consuming task for sleep experts and is limited by inter-rater reliability. In this paper, we propose ... More
Deep Learning in Medical Image Registration: A SurveyMar 05 2019The establishment of image correspondence through robust image registration is critical to many clinical tasks such as image fusion, organ atlas creation, and tumor growth monitoring, and is a very challenging problem. Since the beginning of the recent ... More
An Efficient Production Process for Extracting Salivary Glands from MosquitoesMar 05 2019Malaria is the one of the leading causes of morbidity and mortality in many developing countries. The development of a highly effective and readily deployable vaccine represents a major goal for world health. There has been recent progress in developing ... More
BacSoft: A Tool to Archive Data on BacteriaMar 05 2019Recently, DNA data storage systems have attracted many researchers worldwide. Motivated by the success stories of such systems, in this work we propose a software called BacSoft to clone the data in a bacterial plasmid by using the concept of genetic ... More
ColourQuant: a high-throughput technique to extract and quantify colour phenotypes from plant imagesMar 05 2019Colour patterning contributes to important plant traits that influence ecological interactions, horticultural breeding, and agricultural performance. High-throughput phenotyping of colour is valuable for understanding plant biology and selecting for traits ... More
Global analysis of a simplified model of anaerobic digestion and a new result for the chemostatMar 04 2019A. Bornh\"oft, R. Hanke-Rauschenbach, and K. Sundmacher, [Nonlinear Dyn., 73 (2013), pp. 535-549] introduced a qualitative simplification to the ADM1 model for anaerobic digestion. We obtain global results for this model by first analyzing the limiting ... More
Feedback Control Principles for Biological Control of Dengue VectorsMar 02 2019Controlling diseases such as dengue fever, chikungunya and zika fever by introduction of the intracellular parasitic bacterium Wolbachia in mosquito populations which are their vectors, is presently quite a promising tool to reduce their spread. While ... More
How to Hallucinate Functional ProteinsMar 01 2019Here we present a novel approach to protein design and phenotypic inference using a generative model for protein sequences. BioSeqVAE, a variational autoencoder variant, can hallucinate syntactically valid protein sequences that are likely to fold and ... More
Contemporary statistical inference for infectious disease models using StanMar 01 2019This paper is concerned with the application of recently developed statistical methods for inference in infectious disease models. We use hierarchical models as well as deterministic and stochastic epidemic processes based upon systems of ordinary differential ... More
Contemporary statistical inference for infectious disease models using StanMar 01 2019Mar 04 2019This paper is concerned with the application of recently developed statistical methods for inference in infectious disease models. We use hierarchical models as well as deterministic and stochastic epidemic processes based upon systems of ordinary differential ... More
Outcome-Driven Clustering of Acute Coronary Syndrome Patients using Multi-Task Neural Network with AttentionMar 01 2019Cluster analysis aims at separating patients into phenotypically heterogenous groups and defining therapeutically homogeneous patient subclasses. It is an important approach in data-driven disease classification and subtyping. Acute coronary syndrome ... More
Deep Learning How to Fit an Intravoxel Incoherent Motion Model to Diffusion-Weighted MRIFeb 28 2019Purpose: This prospective clinical study assesses the feasibility of training a deep neural network (DNN) for intravoxel incoherent motion (IVIM) model fitting to diffusion-weighted magnetic resonance imaging (DW-MRI) data and evaluates its performance. ... More
Lévy like patterns in the small-scale movements of marsupials in an unfamiliar and risky environmentFeb 28 2019We investigate the movement patterns of three different Neotropical marsupials in an unfamiliar and risky environment. Animals are released in a matrix from which they try to reach a patch of forest. Their movements, performed on a small spacial scale, ... More
Deep learning in bioinformatics: introduction, application, and perspective in big data eraFeb 28 2019Deep learning, which is especially formidable in handling big data, has achieved great success in various fields, including bioinformatics. With the advances of the big data era in biology, it is foreseeable that deep learning will become increasingly ... More
A tutorial on group effective connectivity analysis, part 2: second level analysis with PEBFeb 27 2019This tutorial provides a worked example of using Dynamic Causal Modelling (DCM) and Parametric Empirical Bayes (PEB) to characterise inter-subject variability in neural circuitry (effective connectivity). This involves specifying a hierarchical model ... More
A tutorial on group effective connectivity analysis, part 1: first level analysis with DCM for fMRIFeb 27 2019Dynamic Causal Modelling (DCM) is the predominant method for inferring effective connectivity from neuroimaging data. In the 15 years since its introduction, the neural models and statistical routines in DCM have developed in parallel, driven by the needs ... More
Principles of efficient chemotactic pursuitFeb 27 2019In chemotaxis, cells are modulating their migration patterns in response to concentration gradients of a guiding substance. Immune cells are believed to use such chemotactic sensing for remotely detecting and homing in on pathogens. Considering that an ... More
Current knowledge and future research opportunities for modeling annual crop mixtures. A reviewFeb 27 2019Growing mixtures of annual arable crop species or genotypes is a promising way to improve crop production without increasing agricultural inputs. To design optimal crop mixtures, choices of species, genotypes, sowing proportion, plant arrangement, and ... More
Cortical recruitment and functional dynamics in postural control adaptation and habituation during vibratory proprioceptive stimulationFeb 27 2019Maintaining upright posture is a complex task governed by the integration of afferent sensorimotor and visual information with compensatory neuromuscular reactions. The objective of this work was to characterize the visual dependency and functional dynamics ... More
A Deep-learning Approach for Prognosis of Age-Related Macular Degeneration Disease using SD-OCT Imaging BiomarkersFeb 27 2019We propose a hybrid sequential deep learning model to predict the risk of AMD progression in non-exudative AMD eyes at multiple timepoints, starting from short-term progression (3-months) up to long-term progression (21-months). Proposed model combines ... More
Continual Prediction from EHR Data for Inpatient Acute Kidney InjuryFeb 26 2019Acute kidney injury (AKI) commonly occurs in hospitalized patients and can lead to serious medical complications. In order to optimally predict AKI before it develops at any time during a hospital stay, we present a novel framework in which AKI is continually ... More
Fast Approximation of Frequent $k$-mers and Applications to MetagenomicsFeb 26 2019Estimating the abundances of all $k$-mers in a set of biological sequences is a fundamental and challenging problem with many applications in biological analysis. While several methods have been designed for the exact or approximate solution of this problem, ... More
Network-based methods for disease-gene predictionFeb 26 2019We predict disease-genes relations on the Human Interactome network using a methodology that jointly learns functional and connectivity patterns surrounding proteins. Contrary to other data structures, the Interactome is characterized by high incompleteness ... More
Automatic cough detection for portable spirometry system trained on large databaseFeb 26 2019In this work, we give a short introduction on cough detection efforts that were undertaken during the last decade and we describe the solution for automatic cough detection developed for the AioCare portable spirometry system. As the system is intended ... More
A Fully-Automatic Framework for Parkinson's Disease Diagnosis by Multi-Modality ImagesFeb 26 2019Background: Parkinson's disease (PD) is a prevalent long-term neurodegenerative disease. Though the diagnostic criteria of PD are relatively well defined, the current medical imaging diagnostic procedures are expertise-demanding, and thus call for a higher-integrated ... More
Transparency guided ensemble convolutional neural networks for stratification of pseudoprogression and true progression of glioblastoma multiformFeb 26 2019Pseudoprogression (PsP) is an imitation of true tumor progression (TTP) in patients with glioblastoma multiform (GBM). Differentiating them is a challenging and time-consuming task for radiologists. Although deep neural networks can automatically diagnose ... More
Fetus: the radar of maternal stress, a cohort studyFeb 26 2019Objective: We hypothesized that prenatal stress (PS) exerts lasting impact on fetal heart rate (fHR). We sought to validate the presence of such PS signature in fHR by measuring coupling between maternal HR (mHR) and fHR. Study design: Prospective observational ... More
Optimal Clustering with Missing ValuesFeb 26 2019Missing values frequently arise in modern biomedical studies due to various reasons, including missing tests or complex profiling technologies for different omics measurements. Missing values can complicate the application of clustering algorithms, whose ... More
Inverse transport problem in fluorescence ultrasound modulated optical tomography with angularly averaged measurementsFeb 25 2019We consider an inverse transport problem in fluorescence ultrasound modulated optical tomography (fUMOT) with angularly averaged illuminations and measurements. We study the uniqueness and stability of the reconstruction of the absorption coefficient ... More
Discriminative Pattern Mining for Breast Cancer Histopathology Image Classification via Fully Convolutional AutoencoderFeb 22 2019Feb 27 2019Accurate diagnosis of breast cancer in histopathology images is challenging due to the heterogeneity of cancer cell growth as well as of a variety of benign breast tissue proliferative lesions. In this paper, we propose a practical and self-interpretable ... More
Interpreting, forecasting, and controlling feeding behaviour using high-resolution dataFeb 22 2019Better understanding of feeding behaviour will be vital in reducing obesity and metabolic syndrome, but we lack a standard model that captures the complexity of feeding behaviour. We construct an accurate stochastic model of rodent feeding at the bout ... More
Interpreting, forecasting, and controlling feeding behaviour using high-resolution dataFeb 22 2019Mar 14 2019Better understanding of feeding behaviour will be vital in reducing obesity and metabolic syndrome, but we lack a standard model that captures the complexity of feeding behaviour. We construct an accurate stochastic model of rodent feeding at the bout ... More
Density distributions and depth in flocksFeb 21 2019Recent experimental evidence suggests that interactions in flocks of birds do not involve a characteristic length scale. Bird flocks have also been revealed to have an inhomogeneous density distribution, with the density of birds near the border greater ... More
A Nonparametric Multi-view Model for Estimating Cell Type-Specific Gene Regulatory NetworksFeb 21 2019We present a Bayesian hierarchical multi-view mixture model termed Symphony that simultaneously learns clusters of cells representing cell types and their underlying gene regulatory networks by integrating data from two views: single-cell gene expression ... More
Classification of diffusion modes in single particle tracking data: feature based vs. deep learning approachFeb 21 2019Feb 26 2019Single-particle trajectories measured in microscopy experiments contain important information about dynamic processes undergoing in a range of materials including living cells and tissues. However, extracting that information is not a trivial task due ... More
Classification of diffusion modes in single particle tracking data: feature based vs. deep learning approachFeb 21 2019Single-particle trajectories measured in microscopy experiments contain important information about dynamic processes undergoing in a range of materials including living cells and tissues. However, extracting that information is not a trivial task due ... More
Inference of a Multi-Domain Machine Learning Model to Predict Mortality in Hospital Stays for Patients with Cancer upon Febrile Neutropenia OnsetFeb 21 2019Febrile neutropenia (FN) has been associated with high mortality, especially among adults with cancer. Understanding the patient and provider level heterogeneity in FN hospital admissions has potential to inform personalized interventions focused on increasing ... More
Inference of a Multi-Domain Machine Learning Model to Predict Mortality in Hospital Stays for Patients with Cancer upon Febrile Neutropenia OnsetFeb 21 2019Feb 27 2019Febrile neutropenia (FN) has been associated with high mortality, especially among adults with cancer. Understanding the patient and provider level heterogeneity in FN hospital admissions has potential to inform personalized interventions focused on increasing ... More
Quantitative analysis of timing in animal vocal sequencesFeb 20 2019Timing features such as the silence gaps between vocal units -- inter-call intervals (ICIs) -- often correlate with biological information such as context or genetic information. Such correlates between the ICIs and biological information have been reported ... More
Fluid-Structure Interaction for the Classroom: Speed, Accuracy, Convergence, and Jellyfish!Feb 20 2019When is good, good enough? This question lingers in approximation theory and numerical methods as a competition between accuracy and practicality. Numerical Analysis is traditionally where the rubber meets the road: students begin to use numerical algorithms ... More
In Vivo Wireless Sensors for Gut Microbiome Redox MonitoringFeb 20 2019A perturbed gut microbiome has recently been linked with multiple disease processes, yet researchers currently lack tools that can provide in vivo, quantitative, and real-time insight into these processes and associated host-microbe interactions. We propose ... More
The Essential Role of Thermodynamics in metabolic network modeling: physical insights and computational challengesFeb 19 2019Quantitative studies of cell metabolism are often based on large chemical reaction network models. A steady state approach is suited to analyze phenomena on the timescale of cell growth and circumvents the problem of incomplete experimental knowledge ... More
A pharmacokinetic model of lead absorption and calcium competitive dynamicsFeb 17 2019Lead is a naturally-occurring element. It has been known to man for a long time, and it is one of the longest established poisons. The current consensus is that no level of lead exposure should be deemed "safe." New evidence regarding the blood levels ... More
Robust and fast heart rate variability analysis of long and noisy electrocardiograms using neural networks and imagesFeb 16 2019Heart rate variability studies depend on the robust calculation of the tachogram, the heart rate times series, usually by the detection of R peaks in the electrocardiogram (ECG). ECGs however are subject to a number of sources of noise which are difficult ... More
Forecasting the 2017-2018 Yemen Cholera Outbreak with Machine LearningFeb 16 2019The ongoing Yemen cholera outbreak has been deemed one of the worst cholera outbreaks in history, with over a million people impacted and thousands dead. Triggered by a civil war, the outbreak has been shaped by various political, environmental, and epidemiological ... More
Comprehensive review of models and methods for inferences in bio-chemical reaction networksFeb 15 2019Key processes in biological and chemical systems are described by networks of chemical reactions. From molecular biology to biotechnology applications, computational models of reaction networks are used extensively to elucidate their non-linear dynamics. ... More
Critical Transitions in Intensive Care Units: A Sepsis Case StudyFeb 15 2019Progression of complex human diseases is associated with transitions across dynamical regimes. These transitions are often phase transitions that generate early-warning signs and provide insights into the underlying disease-driving mechanism(s). In this ... More
A Categorical Compositional Distributional Modelling for the Language of LifeFeb 13 2019The Categorical Compositional Distributional (DisCoCat) Model is a powerful mathematical model for composing the meaning of sentences in natural languages. Since we can think of biological sequences as the "language of life", it's attempting to apply ... More
A complete data processing workflow for CryoET and subtomogram averagingFeb 11 2019Electron cryotomography (CryoET) is currently the only method capable of visualizing cells in 3D at nanometer resolutions. While modern instruments produce massive amounts of tomography data containing extremely rich structural information, the data processing ... More
Classifying attention deficit hyperactivity disorder in children with non-linearities in actigraphyFeb 10 2019Objective This study provides an objective measure based on actigraphy for Attention Deficit Hyperactivity Disorder (ADHD) diagnosis in children. We search for motor activity features that could allow further investigation into their association with ... More
Inverse Projection Representation and Category Contribution Rate for Robust Tumor RecognitionFeb 09 2019Sparse representation based classification (SRC) methods have achieved remarkable results. SRC, however, still suffer from requiring enough training samples, insufficient use of test samples and instability of representation. In this paper, a stable inverse ... More
IMPACT: Interval-based Multi-pass Proteomic Alignment with Constant TracebackFeb 09 2019Darwin is a genomics co-processor that achieved a 15000x acceleration on long read assembly through innovative hardware and algorithm co-design. Darwins algorithms and hardware implementation were specifically designed for DNA analysis pipelines. This ... More
Intervention Pathway Discovery via Context-Dependent Dynamic Sensitivity AnalysisFeb 08 2019The sensitivity analysis of biological system models can significantly contribute to identifying and explaining influences of internal or external changes on model and its elements. We propose here a comprehensive framework to study sensitivity of intra-cellular ... More
Quality quantification in Systems Engineering from the Qualimetry EyeFeb 08 2019Nowadays, quality definition, assessment, control and prediction cannot easily be missed in systems engineering. One common factor among these activities is quality quantification. Therefore, throughout this paper, the authors focus on the problems relating ... More
Restriction enzymes use a 24 dimensional coding space to recognize 6 base long DNA sequencesFeb 06 2019Restriction enzymes recognize and bind to specific sequences on invading bacteriophage DNA. Like a key in a lock, these proteins require many contacts to specify the correct DNA sequence. Using information theory we develop an equation that defines the ... More
The Parameter Houlihan: a solution to high-throughput identifiability indeterminacy for brutally ill-posed problemsFeb 05 2019One way to interject knowledge into clinically impactful forecasting is to use data assimilation, a nonlinear regression that projects data onto a mechanistic physiologic model, instead of a set of functions, such as neural networks. Such regressions ... More
Hope4Genes: a Hopfield-like class prediction algorithm for transcriptomic dataFeb 05 2019After its introduction in 1982, the Hopfield model has been extensively applied for classification and pattern recognition. Recently, its great potential in gene expression patterns retrieval has also been shown. Following this line, we develop Hope4Genes ... More
Adjacency-constrained hierarchical clustering of a band similarity matrix with application to GenomicsFeb 05 2019Motivation: Genomic data analyses such as Genome-Wide Association Studies (GWAS) or Hi-C studies are often faced with the problem of partitioning chromosomes into successive regions based on a similarity matrix of high-resolution, locus-level measurements. ... More
Accurate and robust segmentation of neuroanatomy in T1-weighted MRI by combining spatial priors with deep convolutional neural networksFeb 04 2019Feb 06 2019Neuroanatomical segmentation in magnetic resonance imaging (MRI) of the brain is a prerequisite for volume, thickness and shape measurements. This work introduces a new highly accurate and versatile method based on 3D convolutional neural networks for ... More
Reducing variability in along-tract analysis with diffusion profile realignmentFeb 04 2019Diffusion weighted MRI (dMRI) provides a non invasive virtual reconstruction of the brain's white matter structures through tractography. Analyzing dMRI measures along the trajectory of white matter bundles can provide a more specific investigation than ... More
Machine Learning for Seizure Type Classification: Setting the benchmarkFeb 04 2019Accurate classification of seizure types plays a crucial role in the treatment and disease management of epileptic patients. Epileptic seizure type not only impacts on the choice of drugs but also on the range of activities a patient can safely engage ... More
GA-Novo: De Novo Peptide Sequencing via Tandem Mass Spectrometry using Genetic AlgorithmFeb 03 2019Proteomics is the large-scale analysis of the proteins. The common method for identifying proteins and characterising their amino acid sequences is to digest the proteins into peptides, analyse the peptides using mass spectrometry and assign the resulting ... More
Cameraless High-throughput 3D Imaging Flow CytometryFeb 02 2019Increasing demand for understanding the vast heterogeneity of cellular phenotypes has driven the development of imaging flow cytometry (IFC), that combines features of flow cytometry with fluorescence and bright field microscopy. IFC combines the throughput ... More
Differentiation of skin incision and laparoscopic trocar insertion via quantifying transient bradycardia measured by electrocardiogramFeb 01 2019Background. Most surgical procedures involve structures deeper than the skin. However, the difference in surgical noxious stimulation between skin incision and laparoscopic trocar insertion is unknown. By analyzing instantaneous heart rate (IHR) calculated ... More
Some Enumeration Problems in the Duplication-Loss Model of Genome RearrangementFeb 01 2019Tandem-duplication-random-loss (TDRL) is an important genome rearrangement operation studied in evolutionary biology. This paper investigates some of the formal properties of TDRL operations on the symmetric group (the space of permutations over an $ ... More
Similar Image Search for Histopathology: SMILYJan 30 2019Feb 06 2019The increasing availability of large institutional and public histopathology image datasets is enabling the searching of these datasets for diagnosis, research, and education. Though these datasets typically have associated metadata such as diagnosis ... More
Pressure Actuated Cellular StructuresJan 30 2019This postdoctoral thesis starts by reviewing the historic development of airplane structures and high lift devices from an engineering point of view. However, the main purpose of this document is the development of a novel concept for shape changing, ... More
GAMer 2: A System for 3D Mesh Processing of Cellular Electron MicrographsJan 29 2019Objective: Recent advances in electron microscopy have, for the first time, enabled imaging of single cells in 3D at a nanometer length scale resolution. An uncharted frontier for in silico biology is the ability to simulate cellular processes using these ... More
Representation Transfer for Differentially Private Drug Sensitivity PredictionJan 29 2019Motivation: Human genomic datasets often contain sensitive information that limits use and sharing of the data. In particular, simple anonymisation strategies fail to provide sufficient level of protection for genomic data, because the data are inherently ... More
Simultaneous prediction of multiple outcomes using revised stacking algorithmsJan 29 2019Motivation: HIV is difficult to treat because its virus mutates at a high rate and mutated viruses easily develop resistance to existing drugs. If the relationships between mutations and drug resistances can be determined from historical data, patients ... More
Unveiling new disease, pathway, and gene associations via multi-scale neural networksJan 28 2019Diseases involve complex processes and modifications to the cellular machinery. The gene expression profile of the affected cells contains characteristic patterns linked to a disease. Hence, biological knowledge pertaining to a disease can be derived ... More
A Quantum-Inspired Method for Three-Dimensional Ligand-Based Virtual ScreeningJan 28 2019Measuring similarity between molecules is an important part of virtual screening (VS) experiments deployed during the early stages of drug discovery. Most widely used methods for evaluating the similarity of molecules use molecular fingerprints to encode ... More
Decomposition of Higher-Order Spectra for Blind Multiple-Input Deconvolution, Pattern Identification and SeparationJan 28 2019Like the ordinary power spectrum, higher-order spectra (HOS) describe signal properties that are invariant under translations in time. Unlike the power spectrum, HOS retain phase information from which details of the signal waveform can be recovered. ... More
Spectral Dynamic Causal Modelling of Resting-State fMRI: Relating Effective Brain Connectivity in the Default Mode Network to GeneticsJan 28 2019Jan 30 2019We conduct a novel imaging genetics study of the Alzheimer's Disease Neuroimaging Initiative based on resting-state fMRI (rs-fMRI) and genetic data obtained from 112 subjects, where each subject is classified as either cognitively normal (CN), as having ... More
Tumor Connectomics: Mapping the intra-tumoral complex interaction networkJan 28 2019Tumors are extremely heterogeneous and comprise of a number of intratumor microenvironments or sub-regions. These tumor microenvironments may interact with eac based on complex high-level relationships, which could provide important insight into the organizational ... More
Discovery of Important Subsequences in Electrocardiogram Beats Using the Nearest Neighbour AlgorithmJan 26 2019The classification of time series data is a well-studied problem with numerous practical applications, such as medical diagnosis and speech recognition. A popular and effective approach is to classify new time series in the same way as their nearest neighbours, ... More
A practical guide to the simultaneous determination of protein structure and dynamics using metainferenceJan 23 2019Accurate protein structural ensembles can be determined with metainference, a Bayesian inference method that integrates experimental information with prior knowledge of the system and deals with all sources of uncertainty and errors as well as with system ... More
The threshold age of Keyfitz' entropyJan 23 2019BACKGROUND Indicators of relative inequality of lifespans are important because they capture the dimensionless shape of aging. They are markers of inequality at the population level and express the uncertainty at the time of death at the individual level. ... More
Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learningJan 23 2019Rapid identification of bacteria is essential to prevent the spread of infectious disease, help combat antimicrobial resistance, and improve patient outcomes. Raman optical spectroscopy promises to combine bacterial detection, identification, and antibiotic ... More
Rapid and cost-effective evaluation of bacterial viability using fluorescence spectroscopyJan 22 2019The fluorescence spectra of bacterial samples stained with SYTO 9 and propidium iodide (PI) were used to monitor bacterial viability. Stained mixtures of live and dead Escherichia coli with proportions of live:dead cells varying from 0 to 100% were measured ... More
A simple mechanochemical model for calcium signalling in embryonic epithelial cellsJan 21 2019Calcium (Ca2+) signalling is one of the most important mechanisms of information propagation in the body. In embryogenesis the interplay between Ca2+ signalling and mechanical forces is critical to the healthy development of an embryo but poorly understood. ... More
The control of brain network dynamics across diverse scales of space and timeJan 21 2019The human brain is composed of distinct regions that are each associated with particular functions and distinct propensities for the control of neural dynamics. However, the relation between these functions and control profiles is poorly understood, as ... More
Dual Graph-Laplacian PCA: A Closed-Form Solution for Bi-clustering to Find "Checkerboard" Structures on Gene Expression DataJan 21 2019In the context of cancer, internal "checkerboard" structures are normally found in the matrices of gene expression data, which correspond to genes that are significantly up- or down-regulated in patients with specific types of tumors. In this paper, we ... More
Fitting 3D Shapes from Partial and Noisy Point Clouds with Evolutionary ComputingJan 20 2019Point clouds obtained from photogrammetry are noisy and incomplete models of reality. We propose an evolutionary optimization methodology that is able to approximate the underlying object geometry on such point clouds. This approach assumes a priori knowledge ... More