Relationship between promoter sequence and its strength in gene expression

In this study, through various tests one theoretical model is presented to describe the relationship between promoter strength and its nucleotide sequence. Our analysis shows that, promoter strength is greatly influenced by nucleotide groups with three adjacent nucleotides in its sequence. Meanwhile, nucleotides in different regions of promoter sequence have different effects on promoter strength. Based on experimental data for {\it E. coli} promoters, our calculations indicate, nucleotides in -10 region, -35 region, and the discriminator region of promoter sequence are more important than those in spacing region for determining promoter strength. With model parameter values obtained by fitting to experimental data, four promoter libraries are theoretically built for the corresponding experimental environments under which data for promoter strength in gene expression has been measured previously

Existence and uniqueness of solution of the differential equation describing the TASEP-LK coupled transport process

In this paper, the existence and uniqueness of solution of a specific differential equation is studied. This equation originates from the description of a coupled process by totally asymmetric simple exclusion process (TASEP) and Langmuir kinetics (LK). In the fields of physics and biology, the properties of the TASEP-LK coupled process have been extensively studied by Monte Carlo simulations and numerical calculations, as well as detailed experiments. However, so far, no rigorous mathematical analysis has been given to the corresponding differential equations, especially their existence and uniqueness of solution. In this paper, using the upper and lower solution method, the existence of solution of the steady state equation is obtained. Then using a generalized maximum principle, we show that the solution constructed from the upper and lower solution method is actually the unique solution in C∞ space. Moreover, the existence and uniqueness of solution of the time dependent differential equation are also obtained in one specific space X\b{eta}. Our results imply that the previous results obtained by numerical calculations and Monte Carlo simulations are theoretically correct, especially the most important phase diagram of particle density along the travel track under different model parameters. The study in this paper provides theoretical foundations for the analysis of TASEP-LK coupled process. At the same time, the methods used in this paper may be instructive for studies about the more general cases of the TASEP-LK process, such as the one with multiple travel tracks or the one with multiple particle species.Comment: This paper has been thoroughly modified and submited again to arXiv by my coauther Jingwei Li. So I think it is betetr for me to withdraw from my account. see arXiv:1905.12235v

Multi-Way Factorization Machine For Sentiment Analysis

Sentiment analysis is a process of learning the relationship between sentiment label and text. The research value of sentiment analysis is two-fold: first, it has a wide range of applications in many sectors and industries, e.g., the industry has flourished due to the proliferation of commercial applications such as using sentiment analysis as an integrated part of customer experience strategy. Second, it offers an array of new challenging problems for research community such as word feature embedding and machine learning. Albeit earlier methods such as Naïve Bayes (NB), Random Forest (RF), k-Nearest-Neighbours (kNN), Support Vector Machine (SVM) and more recent methods such as Deep Learning (DL) methods are effective, they are primarily designed for shorter or longer textual data thus are not able to maintain a robust performance across a variety of text with diverse lengths. In reality, some text is as abbreviated as one single word while others are so pleonastic that are over thousands of words. Moreover, ad hoc combination of feature embedding and learning methods makes it more difficult to choose the right approach for different types of textual data. Undoubtedly an integrated feature embedding and sentiment analysis method is desirable. In this thesis, we introduce multi-way FM as a new method for sentiment analysis accounting for higher-order feature interaction. We demonstrate the performance and flexibility of the FM method to other competing methods by tuning a single parameter to accommodate both shorter Twitter and longer movie review documents