TAILIEUCHUNG - Hypergraph and protein function prediction with gene expression data

The natural way overcoming the information loss of the above assumption is to represent the gene expression data as the hypergraph. Thus, in this paper, the three un-normalized, random walk, and symmetric normalized hypergraph Laplacian based semisupervised learning methods applied to hypergraph constructed from the gene expression data in order to predict the functions of yeast proteins are introduced. | Journal of Automation and Control Engineering Vol. 3, No. 2, April 2015 Hypergraph and Protein Function Prediction with Gene Expression Data Loc Hoang Tran University of Minnesota/Computer Science Department, Minneapolis, USA Email: tran0398@ Linh Hoang Tran Portland State University/ECE Department, Portland, USA Email: linht@ Abstract—Most network-based protein (or gene) function prediction methods are based on the assumption that the labels of two adjacent proteins in the network are likely to be the same. However, assuming the pairwise relationship between proteins or genes is not complete. The information a group of genes that show very similar patterns of expression and tend to have similar functions (. the functional modules) is missed. The natural way overcoming the information loss of the above assumption is to represent the gene expression data as the hypergraph. Thus, in this paper, the three un-normalized, random walk, and symmetric normalized hypergraph Laplacian based semisupervised learning methods applied to hypergraph constructed from the gene expression data in order to predict the functions of yeast proteins are introduced. Experiment results show that the average accuracy performance measures of these three hypergraph Laplacian based semi-supervised learning methods are the same. However, their average accuracy performance measures of these three methods are much greater than the average accuracy performance measures of un-normalized graph Laplacian based semi-supervised learning method (. the baseline method of this paper) applied to gene co-expression network created from the gene expression data. Index Terms—hypergraph Laplacian, protein, function, prediction, semi-supervised learning I. INTRODUCTION Protein function prediction plays a very important role in modern biology. Detecting the function of proteins by biological experiments is very time-consuming and difficult. Hence a lot of computational methods have .

• Sinh học
• Journal of Automation and Control Engineering
• Hypergraph function prediction
• Protein function prediction
• Gene expression data
• Semi supervised learning
• The three un normalized
• Increasing the productivity of automation tool by developing socket
• Automation tool by developing socket
• Auto report generated
• The automation tool
• Abnormality management in industrial automation systems
• Industrial automation systems
• Future industrial automation systems
• Abnormality management approach
• Sliding mode based relative pose synchronous control
• Space autonomous rendezvous
• Relative pose synchronous control
• The control system design
• The sliding mode control law
• Application of pressure control type quasiservo valve
• Force control system
• The quasi servo valve
• The pneumatic cylinder
• Robust vehicle suspension system
• Converting active & passive control
• A vehicle to semi active control system analytically
• Semi Active Vehicle System
• Environmental control of a greenhouse system
• NI embedded systems technology
• The soil moisture
• The Engineering School of Bahrain Polytechnic
• Design of control system for 3D printer
• DSP and FPGA
• Control system for 3D printer
• Closed loop control
• Improving performances of a cement rotary kiln
• A model predictive control solution
• Cement rotary kiln
• Advanced process control
• Model predictive control
• Active learning in motor control and matlab simulation
• Active learning in motor control
• Servo motors of the simulation of neural networks
• Motion of a robot arm
• Redundancy and operation of power control system
• A deep space small probe
• Functions of redundancy
• Power Control Unit
• Closed loop speed control of miniature brushless DC motors
• Closed loop speed control
• Miniature brushless DC motors
• Delta Connected BLDC motors
• Adaptive wavelet backstepping control
• Class of mimo underactuated systems
• Multi input multi output
• Proposed control scheme
• Adaptive backstepping controller
• Hybrid position force control for a stewart platform
• Hybrid position force control
• The work surface
• The stewart platform
• Robust control of double inverted pendulum system
• Double inverted pendulum system
• Reference trajectory control
• The dynamic modeling
• Speech recognition in human computer interactive control
• Computer interactive control
• HTK and Sphinx
• Vietnamese speech recognition
• Human computer interaction
• Command shaped robust control of a flexible spacecraft
• Command shaped robust control
• Strong cross couplings
• Loop shaping design
• Optimal control of vehicle active suspension system
• Vehicle active suspension system
• The active suspension system
• LQR control technique
• Mimo fuzzy control for autonomous mobile robot
• Mimo fuzzy control
• Autonomous mobile robot
• Implementation of multi input multi output
• Reach defined target
• Asynthesis method of robust cascade control system
• Robust cascade control system
• Imposes robust conditions
• Soft oscillation index
• Efficient adaptive fuzzy control scheme for industrial manipulators
• Degree of freedom
• Fuzzy control scheme
• IMO nonlinear second order systems
• Multilevel inverter topology and control techniques
• Reduce electromagnetic interference
• Control strategies employed
• Linear quadratic optimal control problem of stochastic switching systems
• Linear quadratic optimal control problem
• Stochastic switching systems
• Non invariant linear systems
• Investigation of hybrid adaptive control schemes
• Needle free jet injection system
• Hybrid adaptive control schemes
• Needle free jet injection
• Modelling and simulations
• Development of a new algorithm
• Control excitation of particular mode of a building
• Particular mode of a building
• Sliding mode control
• Control of electric motor machine tools
• Self organizing fuzzy logic controller
• Modify the control rule
• The self organizing fuzzy logic controller