A general-purpose signal processing algorithm for biological profiles using only first-order derivative information.

ABSTRACT:

Background

Automatic signal-feature extraction algorithms are crucial for profile processing in bioinformatics. Both baseline drift and noise seriously affect the position and peak area of signals. An efficient algorithm named the derivative passing accumulation (DPA) method for simultaneous baseline correction and signal extraction is presented in this article. It is an efficient method using only the first-order derivatives which are obtained through taking the simple differences.

Results

We developed a new signal feature extracting procedure. The vector representing the discrete first-order derivative was divided into negative and positive parts and then accumulated to build a signal descriptor. The signals and background fluctuations are easily separated according to thi

SUBMITTER: Liu Y 

PROVIDER: S-EPMC6882060 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature