DNA Sequence Visualization

Author(s):  
Hsuan T. Chang

This chapter introduces various visualization (i.e., graphical representation) schemes of symbolic DNA sequences, which are basically represented by character strings in conventional sequence databases. Several visualization schemes are reviewed and their characterizations are summarized for comparison. Moreover, further potential applications based on the visualized sequences are discussed. By understanding the visualization process, the researchers will be able to analyze DNA sequences by designing signal processing algorithms for specific purposes such as sequence alignment, feature extraction, and sequence clustering, etc.

Author(s):  
Hsuan T. Chang

This chapter introduces various visualization (i.e., graphical representation) schemes of symbolic DNA sequences, which are basically represented by character strings in conventional sequence databases. Several visualization schemes are reviewed and their characterizations are summarized for comparison. Moreover, further potential applications based on the visualized sequences are discussed. By understanding the visualization process, the researchers will be able to analyze DNA sequences by designing signal processing algorithms for specific purposes such as sequence alignment, feature extraction, and sequence clustering, etc.


2021 ◽  
pp. 1-15
Author(s):  
Jie Hong ◽  
Xiansheng Qin

Over past two decades, steady-state evoked potentials (SSVEP)-based brain computer interface (BCI) systems have been extensively developed. As we all know, signal processing algorithms play an important role in this BCI. However, there is no comprehensive review of the latest development of signal processing algorithms for SSVEP-based BCI. By analyzing the papers published in authoritative journals in nearly five years, signal processing algorithms of preprocessing, feature extraction and classification modules are discussed in detail. In addition, other aspects existed in this BCI are mentioned. The following key problems are solved. (1) In recent years, which signal processing algorithms are frequently used in each module? (2) Which signal processing algorithms attract more attention in recent years? (3) Which modules are the key to signal processing in BCI field? This information is very important for choosing the appropriate algorithms, and can also be considered as a reference for further research. Simultaneously, we hope that this work can provide relevant BCI researchers with valuable information about the latest trends of signal processing algorithms for SSVEP-based BCI systems.


2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Yinan Yu ◽  
Jian Yang ◽  
Tomas McKelvey ◽  
Borys Stoew

Ultrawideband (UWB) technology has many advantages compared to its narrowband counterpart in many applications. We present a new compact low-cost UWB radar for indoor and through-wall scenario. The focus of the paper is on the development of the signal processing algorithms for ranging and tracking, taking into account the particular properties of the UWB CMOS transceiver and the radiation characteristics of the antennas. Theoretical analysis for the algorithms and their evaluations by measurements are presented in the paper. The ranging resolution of this UWB radar has achieved 1-2 mm RMS accuracy for a moving target in indoor environment over a short range, and Kalman tracking algorithm functions well for the through-wall detection.


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