3,159 results match your criteria networks biologically


Learning a genome-wide score of human-mouse conservation at the functional genomics level.

Nat Commun 2021 05 3;12(1):2495. Epub 2021 May 3.

Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA.

Identifying genomic regions with functional genomic properties that are conserved between human and mouse is an important challenge in the context of mouse model studies. To address this, we develop a method to learn a score of evidence of conservation at the functional genomics level by integrating information from a compendium of epigenomic, transcription factor binding, and transcriptomic data from human and mouse. The method, Learning Evidence of Conservation from Integrated Functional genomic annotations (LECIF), trains neural networks to generate this score for the human and mouse genomes. Read More

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The Coronavirus Network Explorer: mining a large-scale knowledge graph for effects of SARS-CoV-2 on host cell function.

BMC Bioinformatics 2021 May 3;22(1):229. Epub 2021 May 3.

Digital Insights, QIAGEN, Redwood City, USA.

Background: Leveraging previously identified viral interactions with human host proteins, we apply a machine learning-based approach to connect SARS-CoV-2 viral proteins to relevant host biological functions, diseases, and pathways in a large-scale knowledge graph derived from the biomedical literature. Our goal is to explore how SARS-CoV-2 could interfere with various host cell functions, and to identify drug targets amongst the host genes that could potentially be modulated against COVID-19 by repurposing existing drugs. The machine learning model employed here involves gene embeddings that leverage causal gene expression signatures curated from literature. Read More

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Application of adverse outcome pathway networks to integrate mechanistic data informing the choice of a point of departure for hydrogen sulfide exposure limits.

Crit Rev Toxicol 2021 Apr 27:1-16. Epub 2021 Apr 27.

ExxonMobil Biomedical Sciences, Inc., Annandale, NJ, USA.

Acute exposure to hydrogen sulfide initiates a series of hallmark biological effects that occur progressively at increasing exposure levels: odor perception, conjunctivitis, olfactory paralysis, "knockdown," pulmonary edema, and apnea. Although effects of exposure to high concentrations of hydrogen sulfide are clear, effects associated with chronic, low-level exposure in humans is under debate, leading to uncertainty in the critical effect used in regulatory risk assessments addressing low dose exposures. This study integrates experimental animal, observational epidemiology, and occupational exposure evidence by applying a pathway-based approach. Read More

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Coupled oscillation and spinning of photothermal particles in Marangoni optical traps.

Proc Natl Acad Sci U S A 2021 May;118(18)

Department of Polymer Science and Engineering, University of Massachusetts, Amherst, MA 01003;

Cyclic actuation is critical for driving motion and transport in living systems, ranging from oscillatory motion of bacterial flagella to the rhythmic gait of terrestrial animals. These processes often rely on dynamic and responsive networks of oscillators-a regulatory control system that is challenging to replicate in synthetic active matter. Here, we describe a versatile platform of light-driven active particles with interaction geometries that can be reconfigured on demand, enabling the construction of oscillator and spinner networks. Read More

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Temporal Coding in Spiking Neural Networks With Alpha Synaptic Function: Learning With Backpropagation.

IEEE Trans Neural Netw Learn Syst 2021 Apr 26;PP. Epub 2021 Apr 26.

The timing of individual neuronal spikes is essential for biological brains to make fast responses to sensory stimuli. However, conventional artificial neural networks lack the intrinsic temporal coding ability present in biological networks. We propose a spiking neural network model that encodes information in the relative timing of individual spikes. Read More

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Constraint-based metabolic control analysis for rational strain engineering.

Metab Eng 2021 Apr 22;66:191-203. Epub 2021 Apr 22.

Laboratory of Computational Systems Biology (LCSB), EPFL, CH-1015, Lausanne, Switzerland. Electronic address:

The advancements in genome editing techniques over the past years have rekindled interest in rational metabolic engineering strategies. While Metabolic Control Analysis (MCA) is a well-established method for quantifying the effects of metabolic engineering interventions on flows in metabolic networks and metabolite concentrations, it does not consider the physiological limitations of the cellular environment and metabolic engineering design constraints. We report here a constraint-based framework, Network Response Analysis (NRA), for rational genetic strain design. Read More

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Comparison of Artificial and Spiking Neural Networks on Digital Hardware.

Front Neurosci 2021 6;15:651141. Epub 2021 Apr 6.

APT Group, Department of Computer Science, University of Manchester, Manchester, United Kingdom.

Despite the success of Deep Neural Networks-a type of Artificial Neural Network (ANN)-in problem domains such as image recognition and speech processing, the energy and processing demands during both training and deployment are growing at an unsustainable rate in the push for greater accuracy. There is a temptation to look for radical new approaches to these applications, and one such approach is the notion that replacing the abstract neuron used in most deep networks with a more biologically-plausible spiking neuron might lead to savings in both energy and resource cost. The most common spiking networks use neurons for which a simple translation from a pre-trained ANN to an equivalent spike-based network (SNN) is readily achievable. Read More

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Self-Assembly of Single Diamond Surface Networks.

Angew Chem Int Ed Engl 2021 Apr 22. Epub 2021 Apr 22.

Tongji University, School of Chemical Science and Engineering, 1239 Siping Road, 200092, Shanghai, CHINA.

Biological scaffolds with hyperbolic surfaces, especially single gyroid and single diamond structures, have sparked immense interest for creating novel materials due to their extraordinary physical properties. However, the ability of nature to create these unbalanced surfaces has not been achieved in either lyotropic liquid crystals or block copolymer phases due to their thermodynamical instability in these systems. Here, we report the synthesis of a porous silica scaffold with a single diamond surface structure fabricated by self-assembly of the poly(ethylene oxide)- b -polystyrene- b -poly( L -lactide) and silica precursors in a mixed solvent of tetrahydrofuran and water. Read More

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Genomics-Guided Drawing of Molecular and Pathophysiological Components of Malignant Regulatory Signatures Reveals a Pivotal Role in Human Diseases of Stem Cell-Associated Retroviral Sequences and Functionally-Active hESC Enhancers.

Front Oncol 2021 31;11:638363. Epub 2021 Mar 31.

Institute of Engineering in Medicine, University of California, San Diego, CA, United States.

Repetitive DNA sequences (repeats) colonized two-third of human genome and a majority of repeats comprised of transposable genetic elements (TE). Evolutionary distinct categories of TE represent nucleic acid sequences that are repeatedly copied from and pasted into chromosomes at multiple genomic locations and acquired a multitude of regulatory functions. Here, genomics-guided maps of stemness regulatory signatures were drawn to dissect the contribution of TE to clinical manifestations of malignant phenotypes of human cancers. Read More

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Inflexible Updating of the Self-Other Divide During a Social Context in Autism; Psychophysical, Electrophysiological, and Neural Network Modeling Evidence.

Biol Psychiatry Cogn Neurosci Neuroimaging 2021 Apr 9. Epub 2021 Apr 9.

Vanderbilt Brain Institute, Vanderbilt University, Nashville, USA; Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, USA; Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, USA.

Background: Autism spectrum disorder (ASD) affects many aspects of life, from social interactions to (multi)sensory processing. Similarly, the condition expresses at the variety of levels of description, from genetics to neural circuits and interpersonal behavior. We attempt to bridge between domains and levels of description by detailing the behavioral, electrophysiological, and putative neural network basis of peri-personal space (PPS) updating in ASD during a social context, given that the encoding of this space relies on appropriate multisensory integration, is malleable by social context, and thought to delineate the boundary between self and other. Read More

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Spike-Timing-Dependent Plasticity With Activation-Dependent Scaling for Receptive Fields Development.

IEEE Trans Neural Netw Learn Syst 2021 Apr 12;PP. Epub 2021 Apr 12.

Spike-timing-dependent plasticity (STDP) is one of the most popular and deeply biologically motivated forms of unsupervised Hebbian-type learning. In this article, we propose a variant of STDP extended by an additional activation-dependent scale factor. The consequent learning rule is an efficient algorithm, which is simple to implement and applicable to spiking neural networks (SNNs). Read More

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Integrated Multi-Omic Analyses of the Genomic Modifications by Gut Microbiome-Derived Metabolites of Epicatechin, 5-(4'-Hydroxyphenyl)-γ-Valerolactone, in TNFalpha-Stimulated Primary Human Brain Microvascular Endothelial Cells.

Front Neurosci 2021 26;15:622640. Epub 2021 Mar 26.

INRAE, UNH, Université Clermont Auvergne, St Genes Champanelle, France.

Cerebral blood vessels are lined with endothelial cells and form the blood-brain barrier. Their dysfunction constitutes a crucial event in the physiopathology of neurodegenerative disorders and cognitive impairment. Epicatechin can improve cognitive functions and lower the risk for Alzheimer's disease or stroke. Read More

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A biomimetic neural encoder for spiking neural network.

Nat Commun 2021 04 9;12(1):2143. Epub 2021 Apr 9.

Department of Engineering Science and Mechanics, Pennsylvania State University, University Park, PA, USA.

Spiking neural networks (SNNs) promise to bridge the gap between artificial neural networks (ANNs) and biological neural networks (BNNs) by exploiting biologically plausible neurons that offer faster inference, lower energy expenditure, and event-driven information processing capabilities. However, implementation of SNNs in future neuromorphic hardware requires hardware encoders analogous to the sensory neurons, which convert external/internal stimulus into spike trains based on specific neural algorithm along with inherent stochasticity. Unfortunately, conventional solid-state transducers are inadequate for this purpose necessitating the development of neural encoders to serve the growing need of neuromorphic computing. Read More

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Bioelectric signaling: Reprogrammable circuits underlying embryogenesis, regeneration, and cancer.

Authors:
Michael Levin

Cell 2021 Apr 6;184(8):1971-1989. Epub 2021 Apr 6.

Allen Discovery Center at Tufts University, Medford, MA, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA. Electronic address:

How are individual cell behaviors coordinated toward invariant large-scale anatomical outcomes in development and regeneration despite unpredictable perturbations? Endogenous distributions of membrane potentials, produced by ion channels and gap junctions, are present across all tissues. These bioelectrical networks process morphogenetic information that controls gene expression, enabling cell collectives to make decisions about large-scale growth and form. Recent progress in the analysis and computational modeling of developmental bioelectric circuits and channelopathies reveals how cellular collectives cooperate toward organ-level structural order. Read More

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A machine learning framework for the prediction of chromatin folding in using epigenetic features.

PeerJ Comput Sci 2020 30;6:e307. Epub 2020 Nov 30.

Skolkovo Institute of Science and Technology, Moscow, Russia.

Technological advances have lead to the creation of large epigenetic datasets, including information about DNA binding proteins and DNA spatial structure. Hi-C experiments have revealed that chromosomes are subdivided into sets of self-interacting domains called Topologically Associating Domains (TADs). TADs are involved in the regulation of gene expression activity, but the mechanisms of their formation are not yet fully understood. Read More

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November 2020

Robust Cortical Thickness Morphometry of Neonatal Brain and Systematic Evaluation Using Multi-Site MRI Datasets.

Front Neurosci 2021 17;15:650082. Epub 2021 Mar 17.

Department of Neurology, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.

The human brain grows the most dramatically during the perinatal and early post-natal periods, during which pre-term birth or perinatal injury that may alter brain structure and lead to developmental anomalies. Thus, characterizing cortical thickness of developing brains remains an important goal. However, this task is often complicated by inaccurate cortical surface extraction due to small-size brains. Read More

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Utilization of Isoflavones in Soybeans for Women with Menopausal Syndrome: An Overview.

Int J Mol Sci 2021 Mar 22;22(6). Epub 2021 Mar 22.

Department of Obstetrics and Gynecology, Taipei Tzu-Chi Hospital, The Buddhist Tzu-Chi Medical Foundation, Taipei 231, Taiwan.

Based on their nutrient composition, soybeans and related foods have been considered to be nutritious and healthy for humans. Particularly, the biological activity and subsequent benefits of soy products may be associated with the presence of isoflavone in soybeans. As an alternative treatment for menopause-related symptoms, isoflavone has gained much popularity for postmenopausal women who have concerns related to undergoing hormone replacement therapy. Read More

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Computation of the electroencephalogram (EEG) from network models of point neurons.

PLoS Comput Biol 2021 Apr 2;17(4):e1008893. Epub 2021 Apr 2.

Neural Coding Laboratory, Istituto Italiano di Tecnologia, Genova, Italy.

The electroencephalogram (EEG) is a major tool for non-invasively studying brain function and dysfunction. Comparing experimentally recorded EEGs with neural network models is important to better interpret EEGs in terms of neural mechanisms. Most current neural network models use networks of simple point neurons. Read More

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Forecasting early onset diminished ovarian reserve for young reproductive age women.

J Assist Reprod Genet 2021 Mar 30. Epub 2021 Mar 30.

Colorado Center for Reproductive Medicine, Lone Tree, Colorado, 80124, USA.

Purpose: To investigate the biological networks associated with DOR in young women and the subsequent molecular impact on preimplantation embryos.

Methods: Whole peripheral blood was collected from patients: young women presenting with diminished ovarian reserve (DOR) and age-matched young women with normal ovarian reserve. Maternal exome sequencing was performed on the NovaSEQ 6000 and sequencing validation was completed using Taqman® SNP Genotyping Assays. Read More

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Dynamic Bayesian Networks for Integrating Multi-omics Time Series Microbiome Data.

mSystems 2021 03 30;6(2). Epub 2021 Mar 30.

Florida International University, Biomolecular Sciences Institute, Miami, Florida, USA.

A key challenge in the analysis of longitudinal microbiome data is the inference of temporal interactions between microbial taxa, their genes, the metabolites that they consume and produce, and host genes. To address these challenges, we developed a computational pipeline, a pipeline for the analysis of longitudinal multi-omics data (PALM), that first aligns multi-omics data and then uses dynamic Bayesian networks (DBNs) to reconstruct a unified model. Our approach overcomes differences in sampling and progression rates, utilizes a biologically inspired multi-omic framework, reduces the large number of entities and parameters in the DBNs, and validates the learned network. Read More

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Designing Biological Circuits: Synthetic Biology Within the Operon Model and Beyond.

Annu Rev Biochem 2021 Mar 30. Epub 2021 Mar 30.

Department of Biological Engineering, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA; email:

In 1961, Jacob and Monod proposed the operon model of gene regulation. At the model's core was the modular assembly of regulators, operators, and structural genes. To illustrate the composability of these elements, Jacob and Monod linked phenotypic diversity to the architectures of regulatory circuits. Read More

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On the limits of active module identification.

Brief Bioinform 2021 Mar 29. Epub 2021 Mar 29.

Chair of Experimental Bioinformatics, Technical University of Munich, Freising, Germany.

In network and systems medicine, active module identification methods (AMIMs) are widely used for discovering candidate molecular disease mechanisms. To this end, AMIMs combine network analysis algorithms with molecular profiling data, most commonly, by projecting gene expression data onto generic protein-protein interaction (PPI) networks. Although active module identification has led to various novel insights into complex diseases, there is increasing awareness in the field that the combination of gene expression data and PPI network is problematic because up-to-date PPI networks have a very small diameter and are subject to both technical and literature bias. Read More

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Tooth Repair and Regeneration: Potential of Dental Stem Cells.

Trends Mol Med 2021 May 26;27(5):501-511. Epub 2021 Mar 26.

Department of Orthodontics, Division of Craniofacial and Molecular Genetics, Tufts University School of Dental Medicine, Boston, MA, USA. Electronic address:

Tooth defects are an extremely common health condition that affects millions of individuals. Currently used dental repair treatments include fillings for caries, endodontic treatment for pulp necrosis, and dental implants to replace missing teeth, all of which rely on the use of synthetic materials. By contrast, the fields of tissue engineering and regenerative medicine and dentistry (TERMD) use biologically based therapeutic strategies for vital tissue regeneration, and thus have the potential to regenerate living tissues. Read More

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Transdiagnostic neuroimaging markers of psychiatric risk: A narrative review.

Neuroimage Clin 2021 Mar 17;30:102634. Epub 2021 Mar 17.

Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom.

Several decades of neuroimaging research in psychiatry have shed light on structural and functional neural abnormalities associated with individual psychiatric disorders. However, there is increasing evidence for substantial overlap in the patterns of neural dysfunction seen across disorders, suggesting that risk for psychiatric illness may be shared across diagnostic boundaries. Gaining insights on the existence of shared neural mechanisms which may transdiagnostically underlie psychopathology is important for psychiatric research in order to tease apart the unique and common aspects of different disorders, but also clinically, so as to help identify individuals early on who may be biologically vulnerable to psychiatric disorder in general. Read More

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Neuronal-Plasticity and Reward-Propagation Improved Recurrent Spiking Neural Networks.

Front Neurosci 2021 12;15:654786. Epub 2021 Mar 12.

Research Center for Brain-Inspired Intelligence, Institute of Automation, Chinese Academy of Sciences (CASIA), Beijing, China.

Different types of dynamics and plasticity principles found through natural neural networks have been well-applied on Spiking neural networks (SNNs) because of their biologically-plausible efficient and robust computations compared to their counterpart deep neural networks (DNNs). Here, we further propose a special Neuronal-plasticity and Reward-propagation improved Recurrent SNN (NRR-SNN). The historically-related adaptive threshold with two channels is highlighted as important neuronal plasticity for increasing the neuronal dynamics, and then global labels instead of errors are used as a reward for the paralleling gradient propagation. Read More

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Gene regulatory networks exhibit several kinds of memory: quantification of memory in biological and random transcriptional networks.

iScience 2021 Mar 1;24(3):102131. Epub 2021 Feb 1.

Allen Discovery Center, Tufts University, Medford, MA, USA.

Gene regulatory networks (GRNs) process important information in developmental biology and biomedicine. A key knowledge gap concerns how their responses change over time. Hypothesizing long-term changes of dynamics induced by transient prior events, we created a computational framework for defining and identifying diverse types of memory in candidate GRNs. Read More

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Unsupervised Learning and Clustered Connectivity Enhance Reinforcement Learning in Spiking Neural Networks.

Front Comput Neurosci 2021 4;15:543872. Epub 2021 Mar 4.

Institute of Neuroscience and Medicine (INM-6) & Institute for Advanced Simulation (IAS-6) & JARA-Institute Brain Structure-Function Relationship (JBI-1 / INM-10), Research Centre Jülich, Jülich, Germany.

Reinforcement learning is a paradigm that can account for how organisms learn to adapt their behavior in complex environments with sparse rewards. To partition an environment into discrete states, implementations in spiking neuronal networks typically rely on input architectures involving place cells or receptive fields specified by the researcher. This is problematic as a model for how an organism can learn appropriate behavioral sequences in unknown environments, as it fails to account for the unsupervised and self-organized nature of the required representations. Read More

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Integrating Non-spiking Interneurons in Spiking Neural Networks.

Front Neurosci 2021 5;15:633945. Epub 2021 Mar 5.

SDU Biorobotics, Maersk McKinney Moller Institute, University of Southern Denmark, Odense, Denmark.

Researchers working with neural networks have historically focused on either non-spiking neurons tractable for running on computers or more biologically plausible spiking neurons typically requiring special hardware. However, in nature homogeneous networks of neurons do not exist. Instead, spiking and non-spiking neurons cooperate, each bringing a different set of advantages. Read More

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FunHoP - Enhanced Visualization and Analysis of Functionally Homologous Proteins in Complex Metabolic Networks.

Genomics Proteomics Bioinformatics 2021 Mar 16. Epub 2021 Mar 16.

Department of Clinical and Molecular Medicine, NTNU - Norwegian University of Science and Technology, NO-7491 Trondheim, Norway; Clinic of Surgery, St. Olavs Hospital, Trondheim University Hospital, NO-7030 Trondheim, Norway. Electronic address:

Cytoscape is often used for visualization and analysis of metabolic pathways. For example, based on KEGG data, a reader for KEGG Markup Language (KGML) is used to load files into Cytoscape. However, although multiple genes can be responsible for the same reaction, the KGML-reader KEGGScape only presents the first listed gene in a network node for a given reaction. Read More

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Regular spiking in high-conductance states: The essential role of inhibition.

Phys Rev E 2021 Feb;103(2-1):022408

Institute of Physiology of the Czech Academy of Sciences, 14220 Prague, Czech Republic.

Strong inhibitory input to neurons, which occurs in balanced states of neural networks, increases synaptic current fluctuations. This has led to the assumption that inhibition contributes to the high spike-firing irregularity observed in vivo. We used single compartment neuronal models with time-correlated (due to synaptic filtering) and state-dependent (due to reversal potentials) input to demonstrate that inhibitory input acts to decrease membrane potential fluctuations, a result that cannot be achieved with simplified neural input models. Read More

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February 2021