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https://www.readbyqxmd.com/read/28716714/functional-density-and-edge-maps-characterizing-functional-architecture-in-individuals-and-improving-cross-subject-registration
#1
Tong Tong, Iman Aganj, Tian Ge, Jonathan R Polimeni, Bruce Fischl
Population-level inferences and individual-level analyses are two important aspects in functional magnetic resonance imaging (fMRI) studies. Extracting reliable and informative features from fMRI data that capture biologically meaningful inter-subject variation is critical for aligning and comparing functional networks across subjects, and connecting the properties of functional brain organization with variations in behavior, cognition and genetics. In this study, we derive two new measures, which we term functional density map and edge map, and demonstrate their usefulness in characterizing the function of individual brains...
July 14, 2017: NeuroImage
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
#2
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
#3
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
#4
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 10, 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
#5
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
#6
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/28709331/scales-and-multimodal-flux-distributions-in-stationary-metabolic-network-models-via-thermodynamics
#7
Daniele De Martino
In this work it is shown that scale-free tails in metabolic flux distributions inferred in stationary models are an artifact due to reactions involved in thermodynamically unfeasible cycles, unbounded by physical constraints and in principle able to perform work without expenditure of free energy. After implementing thermodynamic constraints by removing such loops, metabolic flux distributions scale meaningfully with the physical limiting factors, acquiring in turn a richer multimodal structure potentially leading to symmetry breaking while optimizing for objective functions...
June 2017: Physical Review. E
https://www.readbyqxmd.com/read/28708556/deep-learning-on-sparse-manifolds-for-faster-object-segmentation
#8
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
#9
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
#10
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/28701799/a-robust-method-for-inferring-network-structures
#11
Yang Yang, Tingjin Luo, Zhoujun Li, Xiaoming Zhang, Philip S Yu
Inferring the network structure from limited observable data is significant in molecular biology, communication and many other areas. It is challenging, primarily because the observable data are sparse, finite and noisy. The development of machine learning and network structure study provides a great chance to solve the problem. In this paper, we propose an iterative smoothing algorithm with structure sparsity (ISSS) method. The elastic penalty in the model is introduced for the sparse solution, identifying group features and avoiding over-fitting, and the total variation (TV) penalty in the model can effectively utilize the structure information to identify the neighborhood of the vertices...
July 12, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28700035/excavation-of-attractor-modules-for-nasopharyngeal-carcinoma-via-integrating-systemic-module-inference-with-attract-method
#12
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
#13
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
#14
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/28697314/grainyhead-like-transcription-factors-in-craniofacial-development
#15
M R Carpinelli, M E de Vries, S M Jane, S Dworkin
Craniofacial development in vertebrates involves the coordinated growth, migration, and fusion of several facial prominences during embryogenesis, processes governed by strict genetic and molecular controls. A failure in any of the precise spatiotemporal sequences of events leading to prominence fusion often leads to anomalous facial, skull, and jaw formation-conditions termed craniofacial defects (CFDs). Affecting approximately 0.1% to 0.3% of live births, CFDs are a highly heterogeneous class of developmental anomalies, which are often underpinned by genetic mutations...
July 1, 2017: Journal of Dental Research
https://www.readbyqxmd.com/read/28691371/approaches-to-identify-kinase-dependencies-in-cancer-signalling-networks
#16
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
#17
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/28687508/a-framework-for-the-targeted-selection-of-herbs-with-similar-efficacy-by-exploiting-drug-repositioning-technique-and-curated-biomedical-knowledge
#18
Sang-Jun Yea, Bu-Yeo Kim, Chul Kim, Mun Yong Yi
ETHNO PHARMACOLOGICAL RELEVANCE: Plants have been the most important natural resources for traditional medicine and for the modern pharmaceutical industry. They have been in demand in regards to finding alternative medicinal herbs with similar efficacy. Due to the very low probability of discovering useful compounds by random screening, researchers have advocated for using targeted selection approaches. Furthermore, because drug repositioning can speed up the process of drug development, an integrated technique that exploits chemical, genetic, and disease information has been recently developed...
July 5, 2017: Journal of Ethnopharmacology
https://www.readbyqxmd.com/read/28684624/cell-interactions-signals-and-transcriptional-hierarchy-governing-placode-progenitor-induction
#19
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
https://www.readbyqxmd.com/read/28682266/convolutional-sparse-autoencoders-for-image-classification
#20
Wei Luo, Jun Li, Jian Yang, Wei Xu, Jian Zhang
Convolutional sparse coding (CSC) can model local connections between image content and reduce the code redundancy when compared with patch-based sparse coding. However, CSC needs a complicated optimization procedure to infer the codes (i.e., feature maps). In this brief, we proposed a convolutional sparse auto-encoder (CSAE), which leverages the structure of the convolutional AE and incorporates the max-pooling to heuristically sparsify the feature maps for feature learning. Together with competition over feature channels, this simple sparsifying strategy makes the stochastic gradient descent algorithm work efficiently for the CSAE training; thus, no complicated optimization procedure is involved...
June 29, 2017: IEEE Transactions on Neural Networks and Learning Systems
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