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[1]
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СОВРЕМЕННЫЕ ПОДХОДЫ КЛАССИФИКАЦИИ МЕТОДОВ МОДЕЛИРОВАНИЯ ГЕННЫХ РЕГУЛЯТОРНЫХ СЕТЕЙ
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NULL |
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[2]
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On trajectories of a system modeling evolution of genetic networks
|
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Mathematical Biosciences and …,
2023 |
|
|
|
[3]
|
From time-series transcriptomics to gene regulatory networks: a review on inference methods
|
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arXiv preprint arXiv:2210.08542,
2022 |
|
|
|
[4]
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Integrating steady-state and dynamic gene expression data for improving genetic network modelling
|
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2022 IEEE Conference on …,
2022 |
|
|
|
[5]
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Synchrony patterns in gene regulatory networks
|
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Physica D: Nonlinear Phenomena,
2022 |
|
|
|
[6]
|
Bayesian Copula Directional Dependence for causal inference on gene expression data
|
|
arXiv preprint arXiv:2203.05133,
2022 |
|
|
|
[7]
|
Distributed nonsynchronous event-triggered state estimation of genetic regulatory networks with hidden Markovian jumping parameters
|
|
Mathematical Biosciences and Engineering,
2022 |
|
|
|
[8]
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Stochastic modelling and simulation of PTEN regulatory networks with miRNAs and ceRNAs
|
|
ANNALI DELL'UNIVERSITA'DI FERRARA,
2022 |
|
|
|
[9]
|
A graph model of combination therapies
|
|
Drug Discovery …,
2022 |
|
|
|
[10]
|
Anti-tumor effects of cryptotanshinone (C19H20O3) in human osteosarcoma cell lines
|
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Biomedicine & …,
2022 |
|
|
|
[11]
|
Enhancer RNA (eRNA) in Human Diseases
|
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International Journal of …,
2022 |
|
|
|
[12]
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Quantitative Methods for Precision Medicine: Pharmacogenomics in Action
|
|
2022 |
|
|
|
[13]
|
Remarks on Inhibition
|
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International Journal of Mathematical and …,
2022 |
|
|
|
[14]
|
Models of genetic networks with given properties
|
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WSEAS Transactions on Computer …,
2022 |
|
|
|
[15]
|
Genetic engineering–construction of a network of four dimensions with a chaotic attractor
|
|
Vibroengineering PROCEDIA,
2022 |
|
|
|
[16]
|
Computational network models for molecular, neuronal and brain data in the presence of long range dependence
|
|
2021 |
|
|
|
[17]
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Deciphering the genetic background of quantitative traits using machine learning and bioinformatics frameworks
|
|
2021 |
|
|
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[18]
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Analysis of Topological Properties and Drug Discovery for Bipolar Disorder and Associated Diseases
|
|
2021 |
|
|
|
[19]
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Fused Graphical Lasso Recovers Flowering Time Mutation Genes in Arabidopsis thaliana
|
|
Inventions,
2021 |
|
|
|
[20]
|
Current State of the Problem of Gene Expression Data Processing and Extraction to Solve the Reverse Engineering Tasks in the Field of Bioinformatics.
|
|
2021 |
|
|
|
[21]
|
The Genomic Physics of COVID-19 Pathogenesis and Spread
|
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Cells,
2021 |
|
|
|
[22]
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Revelation of candidate genes and molecular mechanism of reproductive seasonality in female rohu (Labeo rohita Ham.) by RNA sequencing
|
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BMC …,
2021 |
|
|
|
[23]
|
A Static Analysis of Wnt/β-Catenin and Wnt/Ca2+ Biological Regulatory Networks for ARVC Using Automata Network Model
|
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IEEE …,
2021 |
|
|
|
[24]
|
Genetic dissection of growth trajectories in forest trees: From FunMap to FunGraph
|
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Forestry …,
2021 |
|
|
|
[25]
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Application of Meta-Heuristics on Reconstructing Gene Regulatory Network: A Bayesian Model Approach
|
|
2021 |
|
|
|
[26]
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Statistical mechanics of clock gene networks underlying circadian rhythms
|
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2021 |
|
|
|
[27]
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Synchrony in Gene Regulatory Networks
|
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2021 |
|
|
|
[28]
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Modeling genome-wide by environment interactions through omnigenic interactome networks
|
|
2021 |
|
|
|
[29]
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Bayesian Network Analysis of Lysine Biosynthesis Pathway in Rice
|
|
2021 |
|
|
|
[30]
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Recovering dynamic networks in big static datasets
|
|
2021 |
|
|
|
[31]
|
Analysis of topological properties and drug discovery for bipolar disorder and associated diseases: A bioinformatics approach
|
|
2020 |
|
|
|
[32]
|
A remark on attracting sets in genetic regulatory networks
|
|
2020 |
|
|
|
[33]
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Scalable Control of Asynchronous Boolean Networks
|
|
2020 |
|
|
|
[34]
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Detecting Drought Regulators using Stochastic Inference in Bayesian Networks
|
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2020 |
|
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[35]
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Διακλαδώσεις και ευστάθεια λύσεων μοντέλου διαφοροποίησης μεσεγχυματικών στρωματικών/βλαστικών κυττάρων
|
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2020 |
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[36]
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Revelation of candidate genes and molecular mechanism of reproductive seasonality in carp fish (Labeo rohita Ham) by RNA sequencing
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2020 |
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[37]
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Development of mathematical modelling for the glycosylation of IgG in CHO cell cultures
|
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2020 |
|
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[38]
|
Collective predator evasion: Putting the criticality hypothesis to the test
|
|
2020 |
|
|
|
[39]
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CRNet Translator: Building GMA, S-System Models and Chemical Reaction Networks of Disease and Metabolic Pathways
|
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2020 |
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[40]
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Regulatory network analysis of Paneth cell and goblet cell enriched gut organoids using transcriptomics approaches
|
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2020 |
|
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[41]
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ON MODELLING OF ARTIFICIAL NETWORKS ARISING IN APPLICATIONS
|
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2020 |
|
|
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[42]
|
Bayesian Integrative Modeling of Genome-Scale Metabolic and Regulatory Networks
|
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2020 |
|
|
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[43]
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Inference, Dynamics, and Coarse-Graining of Large-Scale Biological Networks
|
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2020 |
|
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[44]
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Dynamical Models of Interrelation in a Class of Artificial Networks
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2019 |
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[45]
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Identification of master regulators in goblet cells and Paneth cells using transcriptomics profiling of gut organoids and multi-layered networks
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2019 |
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[46]
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Systems and Synthetic Biology Approach to Understand the Importance of Host-Pathogen Interaction
|
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2019 |
|
|
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[47]
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A Nullclines Approach to the Study of 2D Artificial Network
|
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2019 |
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[48]
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TIGRNCRN: Trustful Inference of Gene Regulatory Network Using Clustering and Refining the Network
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2019 |
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[49]
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On the Development of the Turtle Scute Pattern and the Origins of its Variation
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2019 |
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[50]
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Integration of probabilistic regulatory networks into constraint-based models of metabolism with applications to Alzheimer's disease
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2019 |
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[51]
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RNAseq analysis reveals drought-responsive molecular pathways with candidate genes and putative molecular markers in root tissue of wheat
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2019 |
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[52]
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Reconstruction of Qualitative Gene Regulatory Networks
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2019 |
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[53]
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Bayesian Inference for Genomic Data Analysis
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2019 |
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[54]
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TIGRNCRN: Trustful inference of gene regulatory network using clustering and refining the network.
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2019 |
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[55]
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Identification and validation of plant miRNA from NGS data—an experimental approach
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Briefings in Functional Genomics,
2018 |
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[56]
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The SQUAD Method for the Qualitative Modeling of Regulatory Networks
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Computational Cell Biology,
2018 |
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[57]
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Networks Describing Dynamical Systems
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2018 |
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[58]
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E. coli gene regulatory networks are inconsistent with gene expression data
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2018 |
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[59]
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Pinning control applied to gene regulatory networks
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2018 |
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[60]
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MICRAT: a novel algorithm for inferring gene regulatory networks using time series gene expression data
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2018 |
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[61]
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A method for estimating Hill function-based dynamic models of gene regulatory networks
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2018 |
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[62]
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Qualitative and semi quantitative systems approaches to complex systems modelling–Intuitive and flexible models of biological systems
|
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2018 |
|
|
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[63]
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Modeling Gene Transcriptional Regulation: A Primer
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Theoretical and Applied Aspects of Systems Biology,
2018 |
|
|
|
[64]
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Modeling of Gene Regulatory Networks
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2018 |
|
|
|
[65]
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Qualitative and semi quantitative systems approaches to complex systems modelling–Intuitive and flexible models of biological systems: A thesis submitted in partial …
|
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2018 |
|
|
|
[66]
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Alternative approach to calculate the structure matrix of Boolean network with semi‐tensor product
|
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IET Control Theory & …,
2017 |
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[67]
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Multivariate Covariance using Principal Component Analysis for Reconstruction of Bidirected Gene Regulatory Networks
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2017 |
|
|
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[68]
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On the distribution of randomly generated boolean networks as models for genetic regulation
|
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2017 |
|
|
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[69]
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Identification of Boolean Networks Using Premined Network Topology Information.
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2017 |
|
|
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[70]
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Towards targeted combinatorial therapy design for the treatment of castration-resistant prostate cancer
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2017 |
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[71]
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Discovery of putative herbicide resistance genes and its regulatory network in chickpea using transcriptome sequencing
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2017 |
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[72]
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Analysis of Gene Expression Discretization Techniques in Microarray Biclustering
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Bioinformatics and Biomedical Engineering,
2017 |
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[73]
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Reverse-engineering biological networks from large data sets
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2017 |
|
|
|
[74]
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An Alternative Approach to Calculate the Structure Matrix of Boolean Network with Semi-Tensor Product
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IET Control Theory & Applications,
2017 |
|
|
|
[75]
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BioCAE: A New Strategy of Complex Biological Systems for Biofabrication of Tissues and Organs
|
|
2017 |
|
|
|
[76]
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Exploring candidate biological functions by Boolean Function Networks for Saccharomyces cerevisiae
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PLOS ONE,
2017 |
|
|
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[77]
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Biological Systems as Heterogeneous Information Networks: A Mini-review and Perspectives
|
|
2017 |
|
|
|
[78]
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Genetic determination and layout rules of visual cortical architecture
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Dissertation,
2017 |
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|
[79]
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Statistical Approach for Functionally Validating Transcription Factor Bindings Using Population SNP and Gene Expression Data
|
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2017 |
|
|
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[80]
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A proposition of Intra-and Interspecies Cell-Cell Communication System
|
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2017 |
|
|
|
[81]
|
Reverse engineering gene regulatory networks from measurement with missing values
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|
2017 |
|
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[82]
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On attractors in gene regulatory systems
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AIP Conference Proceedings,
2017 |
|
|
|
[83]
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Alternative approach to calculate the structure matrix of Boolean network with semi-tensor product
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2017 |
|
|
|
[84]
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Reconstructing Gene Regulation Network based on Conditional Mutual Information
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2017 |
|
|
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[85]
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Using Evolutionary Algorithms for Designing Novel 3D Objects
|
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2017 |
|
|
|
[86]
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On Boolean Modeling of Gene Regulatory Networks for Improved Cancer Combinatorial Therapy Design and Transcriptome Assemblies for Pacific Whiteleg Shrimp
|
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2017 |
|
|
|
[87]
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Discovery of herbicide resistance genes and its regulatory network in chickpea using transcriptome sequencing
|
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2017 |
|
|
|
[88]
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Prediction of oral cancer recurrence using dynamic Bayesian networks
|
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2016 |
|
|
|
[89]
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Perspectives and Networks
|
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2016 |
|
|
|
[90]
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Attracting sets in network regulatory theory
|
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2016 |
|
|
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[91]
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On a differential system arising in the network control theory
|
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2016 |
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[92]
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ON ATTRACTORS IN DYNAMICAL SYSTEMS ARISING IN GENE REGULATORY NETWORK THEORY
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Progress on Difference Equations,
2016 |
|
|
|
[93]
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Boolean modeling techniques for protein co-expression networks in systems medicine
|
|
Expert review of proteomics,
2016 |
|
|
|
[94]
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On a Planar Dynamical System Arising in the Network Control Theory
|
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Mathematical Modelling and Analysis,
2016 |
|
|
|
[95]
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Inference of Gene Regulatory Networks with Neural-Cuckoo Hybrid
|
|
Advanced Computing and Systems for Security,
2016 |
|
|
|
[96]
|
Identification of Boolean Networks Using Premined Network Topology Information
|
|
2016 |
|
|
|
[97]
|
Biological Pathways
|
|
2016 |
|
|
|
[98]
|
Gene Regulatory Network Review
|
|
2016 |
|
|
|
[99]
|
S-system based gene regulatory network reconstruction using Firefly algorithm
|
|
2015 |
|
|
|
[100]
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Experimental and computation approaches reveal mechanisms of evolution of gene regulatory networks underlying echinoderm skeletogenesis
|
|
2015 |
|
|
|
[101]
|
Functional analysis of artificial DNA reaction network
|
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Thèse,
2015 |
|
|
|
[102]
|
A Computational Model Inspired by Gene Regulatory Networks
|
|
2015 |
|
|
|
[103]
|
Neural network based gene regulatory network reconstruction
|
|
Computer, Communication, Control and Information Technology (C3IT), 2015 Third International Conference on,
2015 |
|
|
|
[104]
|
Discretization of gene expression data revised
|
|
Briefings in bioinformatics,
2015 |
|
|
|
[105]
|
NOCTURNAL FRONTAL LOBE EPILEPSY (NFLE): MEDICAL SLEEP DISORDER
|
|
International Conference on Emerging Trends in Technology, Science and Upcoming Research in Computer Science,
2015 |
|
|
|
[106]
|
Integrative computational approaches for studying stem cell differentiation and complex diseases
|
|
2015 |
|
|
|
[107]
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Prediction of tissue-specific effects of gene knockout on apoptosis in different anatomical structures of human brain
|
|
BMC genomics,
2015 |
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|
|
[108]
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Input Dataset Survey of In-Silico Tools for Inference and Visualization of Gene Regulatory Networks (GRN)
|
|
2015 |
|
|
|
[109]
|
Investigating the Role of Network Topology and Dynamical Regimes on the Dynamics of a Cell Differentiation Model
|
|
Advances in Artificial Life and Evolutionary Computation,
2014 |
|
|
|
[110]
|
Clono–Hybrid Algorithm for the Reconstruction of Gene Regulator y Network using S-System
|
|
INTERNATIONAL JOURNAL OF PURE &APPLIED BIOSCIENCE,
2014 |
|
|
|
[111]
|
Modelling approaches for the integration of different omics and database-information for Clostridium acetobutylicum
|
|
2014 |
|
|
|
[112]
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Examples of periodic biological oscillators: transition to a six-dimensional system
|
|
|
|
|
|
[113]
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On a two-dimensional system of differential equations related to the theory of gene regulatory networks
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|
|
|
|
[114]
|
Remark on a system arising in GRN theory
|
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|
|
|
|
[115]
|
Eduards BROKANS
|
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|
|
|
|
[116]
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PLN Y PROCESOS DE INFERENCIA EN LA IDENTIFICACIÓN DE ESTRUCTURAS GENÉTICAS Y SUS MODOS DE REGULACIÓN
|
|
|
|
|
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[117]
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Mathematical modeling of three-dimensional genetic regulatory networks using logistic and Gompertz functions
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