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Computational cell biology

Yulan Liang, Arpad Kelemen
Inferring networks and dynamics of genes, proteins, cells and other biological entities from high-throughput biological omics data is a central and challenging issue in computational and systems biology. This is essential for understanding the complexity of human health, disease susceptibility and pathogenesis for Predictive, Preventive, Personalized and Participatory (P4) system and precision medicine. The delineation of the possible interactions of all genes/proteins in a genome/proteome is a task for which conventional experimental techniques are ill suited...
April 18, 2017: Briefings in Bioinformatics
Y Liu, M Brossard, C Sarnowski, A Vaysse, M Moffatt, P Margaritte-Jeannin, F Llinares-López, M H Dizier, M Lathrop, W Cookson, E Bouzigon, F Demenais
The number of genetic factors associated with asthma remains limited. To identify new genes with an undetected individual effect but collectively influencing asthma risk, we conducted a network-assisted analysis that integrates outcomes of genome-wide association studies (GWAS) and protein-protein interaction networks. We used two GWAS datasets, each consisting of the results of a meta-analysis of nine childhood-onset asthma GWASs (5,924 and 6,043 subjects, respectively). We developed a novel method to compute gene-level P-values (fastCGP), and proposed a parallel dense-module search and cross-selection strategy to identify an asthma-associated gene module...
April 20, 2017: Scientific Reports
Zeinab Hormozi Moghaddam, Manijhe Mokhtari-Dizaji, Mansoureh Movahedin, Mohammad Ehsan Ravari
Considering the use of physical and mechanical stimulation, such as low-intensity ultrasound for proliferation and differentiation of stem cells, it is essential to understand the physical and acoustical mechanisms of acoustic waves in vitro. Mechanical index is used for quantifying acoustic cavitation and the relationship between acoustic pressure and the frequency. In this study, modeling of the mechanical index was applied to provide treatment protocol and to understand the effective physical processes on reproducibility of stem cells...
July 2017: Ultrasonics Sonochemistry
Andrew P Hutchins, Zhongzhou Yang, Yuhao Li, Fangfang He, Xiuling Fu, Xiaoshan Wang, Dongwei Li, Kairong Liu, Jiangping He, Yong Wang, Jiekai Chen, Miguel A Esteban, Duanqing Pei
The current classification of cells in an organism is largely based on their anatomic and developmental origin. Cells types and tissues are traditionally classified into those that arise from the three embryonic germ layers, the ectoderm, mesoderm and endoderm, but this model does not take into account the organization of cell type-specific patterns of gene expression. Here, we present computational models for cell type and tissue specification derived from a collection of 921 RNA-sequencing samples from 272 distinct mouse cell types or tissues...
March 17, 2017: Nucleic Acids Research
Zheng-Wei Li, Zhu-Hong You, Xing Chen, Li-Ping Li, De-Shuang Huang, Gui-Ying Yan, Ru Nie, Yu-An Huang
Identification of protein-protein interactions (PPIs) is of critical importance for deciphering the underlying mechanisms of almost all biological processes of cell and providing great insight into the study of human disease. Although much effort has been devoted to identifying PPIs from various organisms, existing high-throughput biological techniques are time-consuming, expensive, and have high false positive and negative results. Thus it is highly urgent to develop in silico methods to predict PPIs efficiently and accurately in this post genomic era...
April 4, 2017: Oncotarget
Li Min, Cheng Zhang, Like Qu, Jialiang Huang, Lan Jiang, Jiafei Liu, Luca Pinello, Guo-Cheng Yuan, Chengchao Shou
BACKGROUND: Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype. Genome-scale molecular characteristics and regulatory mechanisms that distinguish TNBC from other subtypes remain incompletely characterized. RESULTS: By combining gene expression analysis and PANDA network, we defined three different TF regulatory patterns. A core TNBC-Specific TF Activation Driven Pattern (TNBCac) was specifically identified in TNBC by computational analysis...
March 28, 2017: Oncotarget
Philip J Vance, Gautham P Das, Dermot Kerr, Sonya A Coleman, T Martin McGinnity, Tim Gollisch, Jian K Liu
The processing capabilities of biological vision systems are still vastly superior to artificial vision, even though this has been an active area of research for over half a century. Current artificial vision techniques integrate many insights from biology yet they remain far-off the capabilities of animals and humans in terms of speed, power, and performance. A key aspect to modeling the human visual system is the ability to accurately model the behavior and computation within the retina. In particular, we focus on modeling the retinal ganglion cells (RGCs) as they convey the accumulated data of real world images as action potentials onto the visual cortex via the optic nerve...
April 12, 2017: IEEE Transactions on Neural Networks and Learning Systems
Léon-Charles Tranchevent, Fabien Aubé, Louis Dulaurier, Clara Benoit-Pilven, Amandine Rey, Arnaud Poret, Emilie Chautard, Hussein Mortada, François-Olivier Desmet, Fatima Zahra Chakrama, Maira Alejandra Moreno-Garcia, Evelyne Goillot, Stéphane Janczarski, Franck Mortreux, Cyril F Bourgeois, Didier Auboeuf
Transcriptomic genome-wide analyses demonstrate massive variation of alternative splicing in many physiological and pathological situations. One major challenge is now to establish the biological contribution of alternative splicing variation in physiological- or pathological-associated cellular phenotypes. Toward this end, we developed a computational approach, named Exon Ontology, based on terms corresponding to well-characterized protein features organized in an ontology tree. Exon Ontology is conceptually similar to Gene Ontology-based approaches but focuses on exon-encoded protein features instead of gene level functional annotations...
April 18, 2017: Genome Research
Oren Z Kraus, Ben T Grys, Jimmy Ba, Yolanda Chong, Brendan J Frey, Charles Boone, Brenda J Andrews
Existing computational pipelines for quantitative analysis of high-content microscopy data rely on traditional machine learning approaches that fail to accurately classify more than a single dataset without substantial tuning and training, requiring extensive analysis. Here, we demonstrate that the application of deep learning to biological image data can overcome the pitfalls associated with conventional machine learning classifiers. Using a deep convolutional neural network (DeepLoc) to analyze yeast cell images, we show improved performance over traditional approaches in the automated classification of protein subcellular localization...
April 18, 2017: Molecular Systems Biology
Zhong-Ru Xie, Jiawen Chen, Yinghao Wu
Protein-protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins...
April 18, 2017: Scientific Reports
Elsen Tjhung, Michael E Cates, Davide Marenduzzo
Active fluids are a class of nonequilibrium systems where energy is injected into the system continuously by the constituent particles themselves. Many examples, such as bacterial suspensions and actomyosin networks, are intrinsically chiral at a local scale, so that their activity involves torque dipoles alongside the force dipoles usually considered. Although many aspects of active fluids have been studied, the effects of chirality on them are much less known. Here, we study by computer simulation the dynamics of an unstructured droplet of chiral active fluid in three dimensions...
April 17, 2017: Proceedings of the National Academy of Sciences of the United States of America
Bo Gao, Guojun Li, Juntao Liu, Yang Li, Xiuzhen Huang
It is widely accepted that cancer is driven by accumulated somatic mutations during the lifetime of an individual. Cancer mutations may target relatively small number of cell functional modules. The heterogeneity in different cancer patients makes it difficult to identify driver mutations or functional modules related to cancer. It is biologically desired to be capable of identifying cancer pathway modules through coordination between coverage and exclusivity. There have been a few approaches developed for this purpose, but they all have limitations in practice due to their computational complexity and prediction accuracy...
March 21, 2017: Oncotarget
Xiaolong Li, Zhigao Yi, Zhenluan Xue, Songjun Zeng, Hongrong Liu
Development of high-quality upconversion nanoparticles (UCNPs) with combination of the merits of multiple molecular imaging techniques, such as, upconversion luminescence (UCL) imaging, X-ray computed tomography (CT), and magnetic resonance (MR) imaging, could significantly improve the accuracy of biological diagnosis. In this work, multifunctional BaYbF5: Gd/Er (50:2mol%) UCNPs were synthesized via a solvothermal method using oleic acid (OA) as surface ligands (denoted as OA-UCNPs). The OA-UCNPs were further treated by diluted HCl to form ligand-free UCNPs (LF-UCNPs) for later bioimaging applications...
June 1, 2017: Materials Science & Engineering. C, Materials for Biological Applications
Aboutaleb Amiri, Cameron Harvey, Amy Buchmann, Scott Christley, Joshua D Shrout, Igor S Aranson, Mark Alber
Swarming groups of bacteria coordinate their behavior by self-organizing as a population to move over surfaces in search of nutrients and optimal niches for colonization. Many open questions remain about the cues used by swarming bacteria to achieve this self-organization. While chemical cue signaling known as quorum sensing is well-described, swarming bacteria often act and coordinate on time scales that could not be achieved via these extracellular quorum sensing cues. Here, cell-cell contact-dependent protein exchange is explored as a mechanism of intercellular signaling for the bacterium Myxococcus xanthus...
March 2017: Physical Review. E
Chenglin Liu, Peng Cui, Tao Huang
BACKGROUND: The cell cycle-regulated genes express periodically with the cell cycle stages, and the identification and study of these genes can provide a deep understanding of the cell cycle process. Large false positives and low overlaps are big problems in cell cycle-regulated gene detection. METHODS: Here, a computational framework called DLGene was proposed for cell cycle-regulated gene detection. It is based on the convolutional neural network, a deep learning algorithm representing raw form of data pattern without assumption of their distribution...
April 17, 2017: Combinatorial Chemistry & High Throughput Screening
Robert A Pearlstein, Daniel J J McKay, Viktor Hornak, Callum Dickson, Andrei Golosov, Tyler Harrison, Camilo Velez-Vega, José Duca
Cellular drug targets exist within networked function generating systems whose constituent molecular species undergo dynamic interdependent non-equilibrium state transitions in response to specific perturbations (i.e. inputs). Cellular phenotypic behaviors are manifest through the integrated behaviors of such networks. However, in vitro data are frequently measured and/or interpreted with empirical equilibrium or steady state models (e.g. Hill, Michaelis-Menten, Briggs-Haldane) relevant to isolated target populations...
April 14, 2017: Current Topics in Medicinal Chemistry
Hanxiong Wang, Liping Liu, Dong Liu
The equilibrium shape of a bubble/droplet in an electric field is important for electrowetting over dielectrics (EWOD), electrohydrodynamic (EHD) enhancement for heat transfer and electro-deformation of a single biological cell among others. In this work, we develop a general variational formulation in account of electro-mechanical couplings. In the context of EHD, we identify the free energy functional and the associated energy minimization problem that determines the equilibrium shape of a bubble in an electric field...
March 2017: Proceedings. Mathematical, Physical, and Engineering Sciences
Feng Luan, Lili Tang, Lihong Zhang, Shuang Zhang, Maykel Cruz Monteagudo, M Natália D S Cordeiro
Nanotechnology has led to the development of new nanomaterials with unique properties and a wide variety of applications. In the present study, we focused on the cellular uptake of a group of nanoparticles with a single metal core by pancreatic cancer cells, which has been studied by Yap et al. (Rsc Advances, 2012, 2 (2):8489-8496) using classification models. In this work, the development of a further Quantitative Nanostructure-Activity Relationship (QNAR) model was performed by linear multiple linear regression (MLR) and nonlinear artificial neural network (ANN) techniques to accurately predict the cellular uptake values of these compounds by dividing them into three groups...
April 12, 2017: Food and Chemical Toxicology
Ashima Sinha, Virendra Singh, Savita Yadav
Within the cell, gene expression analysis is the key to gain information about  different cellular and physiological events. The multifaceted route of fertilization is a combination of different processes, which include production, maturation and ejaculation of the sperm, its travel through the female genital tract, followed by the ultimate fusion of the fertile sperm with the egg. Early embryogenesis and gametogenesis as well as gene expression at tissue level and global gene silencing are under different levels of stringent epigenetic checks...
June 1, 2017: Frontiers in Bioscience (Scholar Edition)
Liana Manukyan, Sophie A Montandon, Anamarija Fofonjka, Stanislav Smirnov, Michel C Milinkovitch
In vertebrates, skin colour patterns emerge from nonlinear dynamical microscopic systems of cell interactions. Here we show that in ocellated lizards a quasi-hexagonal lattice of skin scales, rather than individual chromatophore cells, establishes a green and black labyrinthine pattern of skin colour. We analysed time series of lizard scale colour dynamics over four years of their development and demonstrate that this pattern is produced by a cellular automaton (a grid of elements whose states are iterated according to a set of rules based on the states of neighbouring elements) that dynamically computes the colour states of individual mesoscopic skin scales to produce the corresponding macroscopic colour pattern...
April 12, 2017: Nature
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