Determination of k-mer density in a DNA sequence and subsequent cluster formation algorithm based on the application of electronic filter

We describe a novel algorithm for information recovery from DNA sequences by using a digital filter. This work proposes a three-part algorithm to decide the k-mer or q-gram word density. Employing a finite impulse response digital filter, one can calculate the sequence's k-mer or q-gram word density. Further principal component analysis is used on word density distribution to analyze the dissimilarity between sequences. A dissimilarity matrix is thus formed and shows the appearance of cluster formation. This cluster formation is constructed based on the alignment-free sequence method. Furthermore, the clusters are used to build phylogenetic relations. The cluster algorithm is in good agreement with alignment-based algorithms. The present algorithm is simple and requires less time for computation than other currently available algorithms. We tested the algorithm using beta hemoglobin coding sequences (HBB) of 10 different species and 18 primate mitochondria genome (mtDNA) sequences.

Analysis and Design of RF Filters with Lumped and Distributed Elements

Radio frequency (RF) and microwave filters characterize a class of electronic filter, intended to function on signals in the frequency range between megahertz to gigahertz. A Lumped element RF filters is a passive device whose size across any dimension is much smaller than the operating wavelength so that there is minimal change in phase of waveform between the input and output connections. RF filters can also be designed using distributed elements in which all the inductors and the capacitors are replaced by the open and short circuit stubs. This paper concentrates on an analysis and design of low pass filter with the help of only lumped elements and a high pass filter with both lumped and distributed elements.