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Network-based inference

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https://www.readbyqxmd.com/read/28742816/a-mixture-of-sparse-coding-models-explaining-properties-of-face-neurons-related-to-holistic-and-parts-based-processing
#1
Haruo Hosoya, Aapo Hyvärinen
Experimental studies have revealed evidence of both parts-based and holistic representations of objects and faces in the primate visual system. However, it is still a mystery how such seemingly contradictory types of processing can coexist within a single system. Here, we propose a novel theory called mixture of sparse coding models, inspired by the formation of category-specific subregions in the inferotemporal (IT) cortex. We developed a hierarchical network that constructed a mixture of two sparse coding submodels on top of a simple Gabor analysis...
July 25, 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28740825/nmdar-hypofunction-and-somatostatin-expressing-gabaergic-interneurons-and-receptors-a-newly-identified-correlation-and-its-effects-in-schizophrenia
#2
REVIEW
Fatemah Alherz, Mohammad Alherz, Hashemiah Almusawi
This review investigates the association between N-methyl-d-Aspartate receptor (NMDAR) hypofunction and somatostatin-expressing GABAergic interneurons (SST +) and how it contributes to the cognitive deficits observed in schizophrenia (SZ). This is based on evidence that NMDAR antagonists caused symptoms resembling SZ in healthy individuals. NMDAR hypofunction in GABAergic interneurons results in the modulation of the cortical network oscillation, particularly in the gamma range (30-80 Hz). These gamma-band oscillation (GBO) abnormalities were found to lead to the cognitive deficits observed in the disorder...
June 2017: Schizophrenia Research. Cognition
https://www.readbyqxmd.com/read/28739577/common-pitfalls-and-mistakes-in-the-set-up-analysis-and-interpretation-of-results-in-network-meta-analysis-what-clinicians-should-look-for-in-a-published-article
#3
Anna Chaimani, Georgia Salanti, Stefan Leucht, John R Geddes, Andrea Cipriani
OBJECTIVE: Several tools have been developed to evaluate the extent to which the findings from a network meta-analysis would be valid; however, applying these tools is a time-consuming task and often requires specific expertise. Clinicians have little time for critical appraisal, and they need to understand the key elements that help them select network meta-analyses that deserve further attention, optimising time and resources. This paper is aimed at providing a practical framework to assess the methodological robustness and reliability of results from network meta-analysis...
July 24, 2017: Evidence-based Mental Health
https://www.readbyqxmd.com/read/28735000/application-of-pharmacometrics-and-quantitative-systems-pharmacology-to-cancer-therapy-the-example-of-luminal-a-breast-cancer
#4
REVIEW
Brett Fleisher, Kayla Andrews, Ashley A Brown, Sihem Ait-Oudhia
Breast cancer (BC) is the most common cancer in women, and the second most frequent cause of cancer-related deaths in women worldwide. It is a heterogeneous disease composed of multiple subtypes with distinct morphologies and clinical implications. Quantitative systems pharmacology (QSP) is an emerging discipline bridging systems biology with pharmacokinetics (PK) and pharmacodynamics (PD) leveraging the systematic understanding of drugs' efficacy and toxicity. Despite numerous challenges in applying computational methodologies for QSP and mechanism-based PK/PD models to biological, physiological, and pharmacological data, bridging these disciplines has the potential to enhance our understanding of complex disease systems such as BC...
July 19, 2017: Pharmacological Research: the Official Journal of the Italian Pharmacological Society
https://www.readbyqxmd.com/read/28732007/a-data-driven-modeling-approach-to-identify-disease-specific-multi-organ-networks-driving-physiological-dysregulation
#5
Warren D Anderson, Danielle DeCicco, James S Schwaber, Rajanikanth Vadigepalli
Multiple physiological systems interact throughout the development of a complex disease. Knowledge of the dynamics and connectivity of interactions across physiological systems could facilitate the prevention or mitigation of organ damage underlying complex diseases, many of which are currently refractory to available therapeutics (e.g., hypertension). We studied the regulatory interactions operating within and across organs throughout disease development by integrating in vivo analysis of gene expression dynamics with a reverse engineering approach to infer data-driven dynamic network models of multi-organ gene regulatory influences...
July 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28724937/bootstrap-quantification-of-estimation-uncertainties-in-network-degree-distributions
#6
Yulia R Gel, Vyacheslav Lyubchich, L Leticia Ramirez Ramirez
We propose a new method of nonparametric bootstrap to quantify estimation uncertainties in functions of network degree distribution in large ultra sparse networks. Both network degree distribution and network order are assumed to be unknown. The key idea is based on adaptation of the "blocking" argument, developed for bootstrapping of time series and re-tiling of spatial data, to random networks. We first sample a set of multiple ego networks of varying orders that form a patch, or a network block analogue, and then resample the data within patches...
July 19, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28715614/intraperitoneal-administration-of-adipose-tissue-derived-stem-cells-for-the-rescue-of-retinal-degeneration-in-a-mouse-model-via-indigenous-cntf-up-regulation-by-il-6
#7
Jeong Hoon Heo, Jung Ae Yoon, Eun Kyung Ahn, Hyun Kim, Sang Hwa Urm, Chul Oh Oak, Byeng Chul Yu, Sang Joon Lee
As the world's population begins to age, retinal degeneration is an increasing problem, and various treatment modalities are being developed. However, there have been no therapies for degenerative retinal conditions that are not characterized by neovascularization. We investigated whether transplantation of mouse adipose tissue-derived stem cells (mADSC) into the intraperitoneal space has a rescue effect on NaIO3 -induced retinal degeneration in mice. In this study, mADSC transplantation recovered visual function and preserved the retinal outer layer structure compared to the control group without any integration of mADSC into the retina...
July 17, 2017: Journal of Tissue Engineering and Regenerative Medicine
https://www.readbyqxmd.com/read/28713636/ranking-causal-anomalies-via-temporal-and-dynamical-analysis-on-vanishing-correlations
#8
Wei Cheng, Kai Zhang, Haifeng Chen, Guofei Jiang, Zhengzhang Chen, Wei Wang
Modern world has witnessed a dramatic increase in our ability to collect, transmit and distribute real-time monitoring and surveillance data from large-scale information systems and cyber-physical systems. Detecting system anomalies thus attracts significant amount of interest in many fields such as security, fault management, and industrial optimization. Recently, invariant network has shown to be a powerful way in characterizing complex system behaviours. In the invariant network, a node represents a system component and an edge indicates a stable, significant interaction between two components...
August 2016: KDD: Proceedings
https://www.readbyqxmd.com/read/28712570/electron-microscopic-reconstruction-of-functionally-identified-cells-in-a-neural-integrator
#9
Ashwin Vishwanathan, Kayvon Daie, Alexandro D Ramirez, Jeff W Lichtman, Emre R F Aksay, H Sebastian Seung
Neural integrators are involved in a variety of sensorimotor and cognitive behaviors. The oculomotor system contains a simple example, a hindbrain neural circuit that takes velocity signals as inputs and temporally integrates them to control eye position. Here we investigated the structural underpinnings of temporal integration in the larval zebrafish by first identifying integrator neurons using two-photon calcium imaging and then reconstructing the same neurons through serial electron microscopic analysis...
July 24, 2017: Current Biology: CB
https://www.readbyqxmd.com/read/28712341/genetic-analysis-of-bactrocera-zonata-diptera-tephritidae-populations-from-india-based-on-cox1-and-nad1-gene-sequences
#10
Jaipal S Choudhary, Naiyar Naaz, Moanaro Lemtur, Bikash Das, Arun Kumar Singh, Bhagwati P Bhatt, Chandra S Prabhakar
The peach fruit fly, Bactrocera zonata, is among the most serious and polyphagous insect pest of fruit crops in many parts of the world under genus Bactrocera. In the present study, the genetic structure, diversity and demographic history of B. zonata in India were inferred from mitochondrial cytochrome oxidase 1 (cox1) and NADH dehydrogenase 1 (nad1) sequences. The efficiency of DNA barcodes for identification of B. zonata was also tested. Genetic diversity indices [number of haplotypes (H), haplotype diversity (Hd), nucleotide diversity (π) and average number of nucleotide differences (k)] of B...
July 15, 2017: Mitochondrial DNA. Part A. DNA Mapping, Sequencing, and Analysis
https://www.readbyqxmd.com/read/28710402/pagerank-versatility-analysis-of-multilayer-modality-based-network-for-exploring-the-evolution-of-oil-water-slug-flow
#11
Zhong-Ke Gao, Wei-Dong Dang, Shan Li, Yu-Xuan Yang, Hong-Tao Wang, Jing-Ran Sheng, Xiao-Fan Wang
Numerous irregular flow structures exist in the complicated multiphase flow and result in lots of disparate spatial dynamical flow behaviors. The vertical oil-water slug flow continually attracts plenty of research interests on account of its significant importance. Based on the spatial transient flow information acquired through our designed double-layer distributed-sector conductance sensor, we construct multilayer modality-based network to encode the intricate spatial flow behavior. Particularly, we calculate the PageRank versatility and multilayer weighted clustering coefficient to quantitatively explore the inferred multilayer modality-based networks...
July 14, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28708556/deep-learning-on-sparse-manifolds-for-faster-object-segmentation
#12
Jacinto C Nascimento, Gustavo Carneiro
We propose a new combination of deep belief networks and sparse manifold learning strategies for the 2D segmentation of non-rigid visual objects. With this novel combination, we aim to reduce the training and inference complexities while maintaining the accuracy of machine learning based non-rigid segmentation methodologies. Typical non-rigid object segmentation methodologies divide the problem into a rigid detection followed by a non-rigid segmentation, where the low dimensionality of the rigid detection allows for a robust training (i...
July 11, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28705469/systematic-prioritization-of-functional-hotspot-in-rig-1-domains-using-pattern-based-conventional-molecular-dynamic-simulation
#13
P Raghuraman, R Jesu Jaya Sudan, J Lesitha Jeeva Kumari, C Sudandiradoss
BACKGROUND: Retinoic acid inducible gene 1 (RIG-1), multi-domain protein has a role-play in detecting viral nucleic acids and stimulates the antiviral response. Dysfunction of this protein due to mutations makes the route vulnerable to viral diseases. AIM: Identification of functional hotspots that maintains conformational stability in RIG-1 domains. METHODS: In this study, we employed a systematic in silico strategy on RIG-1 protein to understand the mechanism of structural changes upon mutation...
July 10, 2017: Life Sciences
https://www.readbyqxmd.com/read/28702051/random-forest-based-approach-for-maximum-power-point-tracking-of-photovoltaic-systems-operating-under-actual-environmental-conditions
#14
Hussain Shareef, Ammar Hussein Mutlag, Azah Mohamed
Many maximum power point tracking (MPPT) algorithms have been developed in recent years to maximize the produced PV energy. These algorithms are not sufficiently robust because of fast-changing environmental conditions, efficiency, accuracy at steady-state value, and dynamics of the tracking algorithm. Thus, this paper proposes a new random forest (RF) model to improve MPPT performance. The RF model has the ability to capture the nonlinear association of patterns between predictors, such as irradiance and temperature, to determine accurate maximum power point...
2017: Computational Intelligence and Neuroscience
https://www.readbyqxmd.com/read/28700035/excavation-of-attractor-modules-for-nasopharyngeal-carcinoma-via-integrating-systemic-module-inference-with-attract-method
#15
T Jiang, C-Y Jiang, J-H Shu, Y-J Xu
The molecular mechanism of nasopharyngeal carcinoma (NPC) is poorly understood and effective therapeutic approaches are needed. This research aimed to excavate the attractor modules involved in the progression of NPC and provide further understanding of the underlying mechanism of NPC. Based on the gene expression data of NPC, two specific protein-protein interaction networks for NPC and control conditions were re-weighted using Pearson correlation coefficient. Then, a systematic tracking of candidate modules was conducted on the re-weighted networks via cliques algorithm, and a total of 19 and 38 modules were separately identified from NPC and control networks, respectively...
July 10, 2017: Brazilian Journal of Medical and Biological Research, Revista Brasileira de Pesquisas Médicas e Biológicas
https://www.readbyqxmd.com/read/28699566/entity-recognition-from-clinical-texts-via-recurrent-neural-network
#16
Zengjian Liu, Ming Yang, Xiaolong Wang, Qingcai Chen, Buzhou Tang, Zhe Wang, Hua Xu
BACKGROUND: Entity recognition is one of the most primary steps for text analysis and has long attracted considerable attention from researchers. In the clinical domain, various types of entities, such as clinical entities and protected health information (PHI), widely exist in clinical texts. Recognizing these entities has become a hot topic in clinical natural language processing (NLP), and a large number of traditional machine learning methods, such as support vector machine and conditional random field, have been deployed to recognize entities from clinical texts in the past few years...
July 5, 2017: BMC Medical Informatics and Decision Making
https://www.readbyqxmd.com/read/28698475/pedestrian-detection-based-on-adaptive-selection-of-visible-light-or-far-infrared-light-camera-image-by-fuzzy-inference-system-and-convolutional-neural-network-based-verification
#17
Jin Kyu Kang, Hyung Gil Hong, Kang Ryoung Park
A number of studies have been conducted to enhance the pedestrian detection accuracy of intelligent surveillance systems. However, detecting pedestrians under outdoor conditions is a challenging problem due to the varying lighting, shadows, and occlusions. In recent times, a growing number of studies have been performed on visible light camera-based pedestrian detection systems using a convolutional neural network (CNN) in order to make the pedestrian detection process more resilient to such conditions. However, visible light cameras still cannot detect pedestrians during nighttime, and are easily affected by shadows and lighting...
July 8, 2017: Sensors
https://www.readbyqxmd.com/read/28691371/approaches-to-identify-kinase-dependencies-in-cancer-signalling-networks
#18
REVIEW
Maria Dermit, Arran Dokal, Pedro R Cutillas
Cells integrate extracellular signals into appropriate responses through a complex network of biochemical reactions driven by the activity of protein and lipid kinases, among other proteins. In order to understand this complexity, new approaches, both experimental and computational, have recently been developed with the aim to identify regulatory kinases and infer their activation status in the context of their signalling network. Here, we review such approaches with particular focus on those based on phosphoproteomics...
July 10, 2017: FEBS Letters
https://www.readbyqxmd.com/read/28691107/network-based-approaches-that-exploit-inferred-transcription-factor-activity-to-analyze-the-impact-of-genetic-variation-on-gene-expression
#19
Harmen J Bussemaker, Helen C Causton, Mina Fazlollahi, Eunjee Lee, Ivor Muroff
Over the past decade, a number of methods have emerged for inferring protein-level transcription factor activities in individual samples based on prior information about the structure of the gene regulatory network. We discuss how this has enabled new methods for dissecting trans-acting mechanisms that underpin genetic variation in gene expression.
April 2017: Current opinion in systems biology
https://www.readbyqxmd.com/read/28684624/cell-interactions-signals-and-transcriptional-hierarchy-governing-placode-progenitor-induction
#20
Mark Hintze, Ravindra Singh Prajapati, Monica Tambalo, Nicolas A D Christophorou, Maryam Anwar, Timothy Grocott, Andrea Streit
In vertebrates, cranial placodes contribute to all sense organs and sensory ganglia and arsise from a common pool of Six1/Eya2+ progenitors. Here we dissect the events that specify ectodermal cells as placode progenitors using newly identified genes upstream of the Six/Eya complex. We show that two different tissues, the lateral head mesoderm and the prechordal mesendoderm, gradually induce placode progenitors: cells pass through successive transcriptional states, each identified by distinct factors and controlled by different signals...
July 6, 2017: Development
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