LEADER 03488nam 2200781z- 450 001 9910557545803321 005 20210501 035 $a(CKB)5400000000044149 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/68899 035 $a(oapen)doab68899 035 $a(EXLCZ)995400000000044149 100 $a20202105d2020 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aStatistical Methods for the Analysis of Genomic Data 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2020 215 $a1 online resource (136 p.) 311 08$a3-03936-140-6 311 08$a3-03936-141-4 330 $aIn recent years, technological breakthroughs have greatly enhanced our ability to understand the complex world of molecular biology. Rapid developments in genomic profiling techniques, such as high-throughput sequencing, have brought new opportunities and challenges to the fields of computational biology and bioinformatics. Furthermore, by combining genomic profiling techniques with other experimental techniques, many powerful approaches (e.g., RNA-Seq, Chips-Seq, single-cell assays, and Hi-C) have been developed in order to help explore complex biological systems. As a result of the increasing availability of genomic datasets, in terms of both volume and variety, the analysis of such data has become a critical challenge as well as a topic of great interest. Therefore, statistical methods that address the problems associated with these newly developed techniques are in high demand. This book includes a number of studies that highlight the state-of-the-art statistical methods for the analysis of genomic data and explore future directions for improvement. 606 $aMathematics and Science$2bicssc 606 $aResearch and information: general$2bicssc 610 $aBayes factor 610 $aBayesian mixed-effect model 610 $aboosting 610 $aclassification 610 $aclassification boundary 610 $aclustering analysis 610 $aconvolutional neural networks 610 $aCpG sites 610 $adeep learning 610 $aDNA methylation 610 $aexpectation-maximization algorithm 610 $afalse discovery rate control 610 $afeed-forward neural networks 610 $agaussian finite mixture model 610 $aGEE 610 $agene expression 610 $agene regulatory network 610 $agene set enrichment analysis 610 $aintegrative analysis 610 $akernel method 610 $alipid-environment interaction 610 $alongitudinal lipidomics study 610 $amachine learning 610 $amultiple cancer types 610 $an/a 610 $anetwork substructure 610 $anonparanormal graphical model 610 $aomics data 610 $aOrdinal responses 610 $apenalized variable selection 610 $aprognosis modeling 610 $aRNA-seq 610 $auncertainty 615 7$aMathematics and Science 615 7$aResearch and information: general 700 $aJiang$b Hui$4edt$01312123 702 $aHe$b Zhi$4edt 702 $aJiang$b Hui$4oth 702 $aHe$b Zhi$4oth 906 $aBOOK 912 $a9910557545803321 996 $aStatistical Methods for the Analysis of Genomic Data$93030716 997 $aUNINA LEADER 05608nam 22006855 450 001 9910729895903321 005 20260401155914.0 010 $a3-031-28505-0 024 7 $a10.1007/978-3-031-28505-9 035 $a(CKB)26852478000041 035 $a(MiAaPQ)EBC30589115 035 $a(Au-PeEL)EBL30589115 035 $a(OCoLC)1381708228 035 $a(DE-He213)978-3-031-28505-9 035 $a(PPN)272263788 035 $a(EXLCZ)9926852478000041 100 $a20230606d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDifferential Equations, Mathematical Modeling and Computational Algorithms $eDEMMCA 2021, Belgorod, Russia, October 25?29 /$fedited by Vladimir Vasilyev 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (294 pages) 225 1 $aSpringer Proceedings in Mathematics & Statistics,$x2194-1017 ;$v423 311 08$a9783031285042 327 $aV. E. Fedorov and K. V. Boyko, Some Classes of Quasilinear Equations with Gerasimov - Caputo Derivatives -- A. Glushak, On the Solvability of Initial Problems for Abstract Singular Equations Containing Fractional Derivatives -- A. Kulikov and D. Kulikov, Local Bifurcations of Periodic Traveling Waves in the Generalized Weakly Dissipative Ginzburg-Landau Equation -- R. Soren Kraußhar, A. Legatiuk, and D. Legatiuk, Towards discrete octonionic analysis -- Igor S. Lomov, Axiomatic method for constructing a generalized solution of a mixed problem for a telegraph equation -- A. Mironov and L. Mironova, "Non-local Substitutions for Liouville Equations with Three and Four Independent Variables -- Li Liu, Zhenbin Fan, Gang Li, and Sergey Piskarev, Convergence rates of a finite difference method for the fractional subdiffusion equations -- M. Plekhanova and E. Izhberdeeva, Degenerate quasilinear equations with Dzhrbashyan Nersesian derivatives and applications -- Marina V. Polovinkinaand Igor P. Polovinkin, On a K-homogeneous metric -- F. Sadyrbaev, I. Samuilik, and V. Sengileyev, Biooscillators in models of genetic networks -- A. Setukha and S. Stavtsev, Numerical Method for Problem of Scattering by a Small Thickness Dielectric Layer on a Perfectly Conductive Substrate -- Maxim V. Shamolin, Invariants of Dynamical Systems with Dissipation on Tangent Bundles of Low-Dimensional Manifolds -- E. Shishkina, B-subharmonic functions -- S. M. Sitnik, V. Skoromnik and M. V. Papkopvich, Some Multi-Dimensional Modied G- and H-Integral Transforms on Spaces -- B.D. Koshanov and A.P. Soldatov, On sufficient conditions of the Faddeev-Marchenko theorem -- N. Subbotina and E. Krupennikov, Variational approach to construction of piecewise-constant approximations of the solution of dynamic reconstruction problem -- A. Vasilyev, V. Vasilyev, and Asad Esmatullah, Discrete Operators and Equations: Analysis and Comparison -- V. Vasilyev, V. Polunin and I. Shmal, Pseudo-Differential Equations in Spaces of Different Smoothness Exponents on Variables -- Yuri P. Virchenko, Thermodynamic limit in vector lattice models -- N. V. Zaitseva, Family of smooth solutions of a hyperbolic differential-difference equation. 330 $aThis book contains reports made at the International Conference on Differential Equations, Mathematical Modeling and Computational Algorithms, held in Belgorod, Russia, in October 2021 and is devoted to various aspects of the theory of differential equations and their applications in various branches of science. Theoretical papers devoted to the qualitative analysis of emerging mathematical objects, theorems of the existence and uniqueness of solutions to the boundary value problems under study are presented, and numerical algorithms for their solution are described. Some issues of mathematical modeling are also covered; in particular, in problems of economics, computational aspects of the theory of differential equations and boundary value problems are studied. The articles are written by well-known experts and are interesting and useful to a wide audience: mathematicians, representatives of applied sciences and students and postgraduates of universities engaged in applied mathematics. 410 0$aSpringer Proceedings in Mathematics & Statistics,$x2194-1017 ;$v423 606 $aDifferential equations 606 $aMathematical models 606 $aMathematics$xData processing 606 $aDifferential Equations 606 $aMathematical Modeling and Industrial Mathematics 606 $aComputational Science and Engineering 606 $aEquacions diferencials$2thub 606 $aModels matemātics$2thub 606 $aAlgorismes computacionals$2thub 608 $aCongressos$2thub 608 $aLlibres electrōnics$2thub 615 0$aDifferential equations. 615 0$aMathematical models. 615 0$aMathematics$xData processing. 615 14$aDifferential Equations. 615 24$aMathematical Modeling and Industrial Mathematics. 615 24$aComputational Science and Engineering. 615 7$aEquacions diferencials 615 7$aModels matemātics 615 7$aAlgorismes computacionals 676 $a515.35 700 $aVasil?ev$b V. N$g(Vladimir Nikolaevich)$01868401 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910729895903321 996 $aDifferential Equations, Mathematical Modeling and Computational Algorithms$94476302 997 $aUNINA