Literatura académica sobre el tema "Inhibitory Network Model"
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Artículos de revistas sobre el tema "Inhibitory Network Model"
Skinner, F. K., J. Y. J. Chung, I. Ncube, P. A. Murray y S. A. Campbell. "Using Heterogeneity to Predict Inhibitory Network Model Characteristics". Journal of Neurophysiology 93, n.º 4 (abril de 2005): 1898–907. http://dx.doi.org/10.1152/jn.00619.2004.
Texto completoVassiliev, P. M., A. A. Spasov, A. N. Kochetkov, M. A. Perfilev y A. R. Koroleva. "Consensus ensemble neural network multitarget model of RAGE inhibitory activity of chemical compounds". Biomeditsinskaya Khimiya 67, n.º 3 (2021): 268–77. http://dx.doi.org/10.18097/pbmc20216703268.
Texto completoBryson, Alexander, Samuel F. Berkovic, Steven Petrou y David B. Grayden. "State transitions through inhibitory interneurons in a cortical network model". PLOS Computational Biology 17, n.º 10 (15 de octubre de 2021): e1009521. http://dx.doi.org/10.1371/journal.pcbi.1009521.
Texto completoChou, Kenny F. y Kamal Sen. "AIM: A network model of attention in auditory cortex". PLOS Computational Biology 17, n.º 8 (27 de agosto de 2021): e1009356. http://dx.doi.org/10.1371/journal.pcbi.1009356.
Texto completoRich, Scott, Michal Zochowski y Victoria Booth. "Effects of Neuromodulation on Excitatory–Inhibitory Neural Network Dynamics Depend on Network Connectivity Structure". Journal of Nonlinear Science 30, n.º 5 (4 de enero de 2018): 2171–94. http://dx.doi.org/10.1007/s00332-017-9438-6.
Texto completoCao, Ying, Xiaoyan He, Yuqing Hao y Qingyun Wang. "Transition Dynamics of Epileptic Seizures in the Coupled Thalamocortical Network Model". International Journal of Bifurcation and Chaos 28, n.º 08 (julio de 2018): 1850104. http://dx.doi.org/10.1142/s0218127418501043.
Texto completoTiesinga, Paul H. E. "Stimulus Competition by Inhibitory Interference". Neural Computation 17, n.º 11 (1 de noviembre de 2005): 2421–53. http://dx.doi.org/10.1162/0899766054796905.
Texto completoYAMAZAKI, TADASHI y SHIGERU TANAKA. "A NEURAL NETWORK MODEL FOR TRACE CONDITIONING". International Journal of Neural Systems 15, n.º 01n02 (febrero de 2005): 23–30. http://dx.doi.org/10.1142/s0129065705000037.
Texto completoAndreev, Andrey y Vladimir Maksimenko. "Synchronization in coupled neural network with inhibitory coupling". Cybernetics and Physics, Volume 8, 2019, Number 4 (30 de diciembre de 2019): 199–204. http://dx.doi.org/10.35470/2226-4116-2019-8-4-199-204.
Texto completoBlazis, Diana E. J., Thomas M. Fischer y Thomas J. Carew. "A Neural Network Model of Inhibitory Information Processing in Aplysia". Neural Computation 5, n.º 2 (marzo de 1993): 213–27. http://dx.doi.org/10.1162/neco.1993.5.2.213.
Texto completoTesis sobre el tema "Inhibitory Network Model"
Ahn, Sungwoo. "Transient and Attractor Dynamics in Models for Odor Discrimination". The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1280342970.
Texto completoDenecker, Thomas. "Bioinformatique et analyse de données multiomiques : principes et applications chez les levures pathogènes Candida glabrata et Candida albicans Functional networks of co-expressed genes to explore iron homeostasis processes in the pathogenic yeast Candida glabrata Efficient, quick and easy-to-use DNA replication timing analysis with START-R suite FAIR_Bioinfo: a turnkey training course and protocol for reproducible computational biology Label-free quantitative proteomics in Candida yeast species: technical and biological replicates to assess data reproducibility Rendre ses projets R plus accessibles grâce à Shiny Pixel: a content management platform for quantitative omics data Empowering the detection of ChIP-seq "basic peaks" (bPeaks) in small eukaryotic genomes with a web user-interactive interface A hypothesis-driven approach identifies CDK4 and CDK6 inhibitors as candidate drugs for treatments of adrenocortical carcinomas Characterization of the replication timing program of 6 human model cell lines". Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASL010.
Texto completoBiological research is changing. First, studies are often based on quantitative experimental approaches. The analysis and the interpretation of the obtained results thus need computer science and statistics. Also, together with studies focused on isolated biological objects, high throughput experimental technologies allow to capture the functioning of biological systems (identification of components as well as the interactions between them). Very large amounts of data are also available in public databases, freely reusable to solve new open questions. Finally, the data in biological research are heterogeneous (digital data, texts, images, biological sequences, etc.) and stored on multiple supports (paper or digital). Thus, "data analysis" has gradually emerged as a key research issue, and in only ten years, the field of "Bioinformatics" has been significantly changed. Having a large amount of data to answer a biological question is often not the main challenge. The real challenge is the ability of researchers to convert the data into information and then into knowledge. In this context, several biological research projects were addressed in this thesis. The first concerns the study of iron homeostasis in the pathogenic yeast Candida glabrata. The second concerns the systematic investigation of post-translational modifications of proteins in the pathogenic yeast Candida albicans. In these two projects, omics data were used: transcriptomics and proteomics. Appropriate bioinformatics and analysis tools were developed, leading to the emergence of new research hypotheses. Particular and constant attention has also been paid to the question of data reproducibility and sharing of results with the scientific community
Dasgupta, Dabanjan. "Plasticity of Intrinsic Excitability in Fast Spiking Interneurons of the Dentate Gyrus & Its Implications for Neuronal Network Dynamics". Thesis, 2015. https://etd.iisc.ac.in/handle/2005/4079.
Texto completoCapítulos de libros sobre el tema "Inhibitory Network Model"
Dagnew, Tewodros M., Claudio Silvestri, Debora Slanzi y Irene Poli. "A Neural Network Model for Lead Optimization of MMP12 Inhibitors". En Pattern Recognition. ICPR International Workshops and Challenges, 323–35. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68799-1_23.
Texto completoAida, Masaki y Ayako Hashizume. "Activator-Inhibitor Model for Describing Interactions Between Fake News and Their Corrections". En Complex Networks & Their Applications X, 54–65. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93413-2_5.
Texto completoBem, Tiaza y John Hallam. "Characterisation of Multiple Patterns of Activity in Networks of Relaxation Oscillators with Inhibitory and Electrical Coupling". En Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira’s Scientific Legacy, 164–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02264-7_18.
Texto completoKharybina, Zoia. "A Model of Neurodynamics of Hippocampal Formation Neurons Performing Spatial Processing Based on Even Cyclic Inhibitory Networks". En Advances in Intelligent Systems and Computing, 79–84. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32554-5_11.
Texto completoPalop, Jorge J., Lennart Mucke y Erik D. Roberson. "Quantifying Biomarkers of Cognitive Dysfunction and Neuronal Network Hyperexcitability in Mouse Models of Alzheimer’s Disease: Depletion of Calcium-Dependent Proteins and Inhibitory Hippocampal Remodeling". En Methods in Molecular Biology, 245–62. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60761-744-0_17.
Texto completoDe Pauw, Ines, Carolien Boeckx y An Wouters. "Mechanisms of Cetuximab Resistance and How to Overcome It". En Critical Issues in Head and Neck Oncology, 21–51. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63234-2_3.
Texto completoGhosh, Joydeep, Hung-Jen Chang y Kadir Liano. "A Macroscopic Model of Oscillation in Ensembles of Inhibitory and Excitatory Neurons". En Neural Networks and Pattern Recognition, 143–69. Elsevier, 1998. http://dx.doi.org/10.1016/b978-012526420-4/50006-9.
Texto completoTsarouchas, Nick. "Clinical Neurophysiology of Epileptogenic Networks". En Neurophysiology - Networks, Plasticity, Pathophysiology, and Behavior [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.104952.
Texto completoBulashevska, Svetlana. "Inferring Genetic Regulatory Interactions with Bayesian Logic-Based Model". En Handbook of Research on Computational Methodologies in Gene Regulatory Networks, 108–38. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-685-3.ch005.
Texto completoAl-Hajri, Salim y Arthur Tatnall. "A Socio-Technical Study of the Adoption of Internet Technology in Banking, Re-Interpreted as an Innovation Using Innovation Translation". En Social and Professional Applications of Actor-Network Theory for Technology Development, 207–20. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2166-4.ch016.
Texto completoActas de conferencias sobre el tema "Inhibitory Network Model"
Hedayati, B. Keshavarz, R. Parra-Hernandez, E. M. Laxdal, N. J. Dimopoulos, P. Alexiou y V. J. Demopoulos. "An improved neural network ensemble model of Aldose Reductase inhibitory activity". En 2012 International Joint Conference on Neural Networks (IJCNN 2012 - Brisbane). IEEE, 2012. http://dx.doi.org/10.1109/ijcnn.2012.6252798.
Texto completoHui, Qing, Wassim M. Haddad, James M. Bailey y Tomohisa Hayakawa. "A stochastic mean field model for an excitatory and inhibitory synaptic drive cortical neuronal network". En 2012 IEEE 51st Annual Conference on Decision and Control (CDC). IEEE, 2012. http://dx.doi.org/10.1109/cdc.2012.6426144.
Texto completoCannon, Mark W. "A model for spatial interactions among contrast sensitive mechanisms". En OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/oam.1992.thp4.
Texto completoYang, Xiang Y., Taiwei Lu y Francis T. S. Yu. "Generalized interpattern association neural network". En OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1990. http://dx.doi.org/10.1364/oam.1990.mn6.
Texto completoMARNELLOS, G., G. A. DEBLANDRE, E. MJOLSNESS y C. KINTNER. "DELTA-NOTCH LATERAL INHIBITORY PATTERNING IN THE EMERGENCE OF CILIATED CELLS IN XENOPUS: EXPERIMENTAL OBSERVATIONS AND A GENE NETWORK MODEL". En Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 1999. http://dx.doi.org/10.1142/9789814447331_0031.
Texto completoWeible, K. J., N. Collings, W. Xue, G. Pedrini y R. Dändliker. "Experimental comparison of different associative memory techniques implemented optically by the same system architecture". En Optical Computing. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/optcomp.1991.me9.
Texto completoYu, Francis T. S., Taiwei Lu y Xiang Y. Yang. "Optical heteroassociative memory for character translation". En OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1990. http://dx.doi.org/10.1364/oam.1990.mj3.
Texto completoBlake, Randolph y Mark Nawrot. "Stereopsis and kinetic depth: two sides of the same coin?" En OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/oam.1991.fd2.
Texto completoZhang, Tielin, Yi Zeng, Dongcheng Zhao y Bo Xu. "Brain-inspired Balanced Tuning for Spiking Neural Networks". En Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/229.
Texto completoSpooner, Victoria E., Robert Stalker, Rob Wright y Gordon M. Graham. "Improving Scale Inhibitor Squeeze Design for Naturally Fractured Reservoirs". En SPE International Oilfield Scale Conference and Exhibition. SPE, 2014. http://dx.doi.org/10.2118/spe-169755-ms.
Texto completoInformes sobre el tema "Inhibitory Network Model"
Tian, Cong, Jianlong Shu, Wenhui Shao, Zhengxin Zhou, Huayang Guo y Jingang Wang. The efficacy and safety of IL Inhibitors, TNF-α Inhibitors, and JAK Inhibitor on ankylosing spondylitis: A Bayesian network meta-analysis of a “randomized, double-blind, placebo-controlled” trials. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, septiembre de 2022. http://dx.doi.org/10.37766/inplasy2022.9.0117.
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