#Biological sequence analysis software#

A complete NGS workflow to generate a consensus sequence and haplotypes is discussed. Biological Sequence Analysis This chapter focuses on several biological sequence analysis techniques used in computational biology and bioinformatics. In this review we discuss the general role of P-value estimation in sequence analysis, and give a description of. Distributed memory building blocks for massive biological sequence analysis dc.subject, Bioinformatics dc.subject, K-mer index dc.subject, K-mer counting dc. Deep sequencing is highly important due to its ability to address an increasingly diverse range of biological problems such as the ones encountered in therapeutics. The statistical significance of an alignment score is frequently assessed by its P-value, which is the probability that this score or a higher one can occur simply by chance, given the probabilistic models for the sequences. Sequence analysis is incomplete without discussing next-generation sequencing (NGS) data.

#Biological sequence analysis software#

This chapter discusses both supervised and unsupervised learning, neural networks, and hidden Markov models. Notably, the problem set includes all of the problems offered in Biological Sequence Analysis (BSA), by Durbin et al., widely adopted as a required text for. It introduces biological sequence analysis problems, discusses the benefit of using software libraries, summarizes the design principles and goals of SeqAn. Artificial intelligence and machine learning methods have been used successfully in analyzing sequence data and have played an important role in elucidating many biological functions, such as protein functional classification, active site recognition, protein structural features identification, and disease prediction outcomes.

Alignment algorithms such as dynamic programming, basic local alignment search tool and HHblits are discussed.

Bioinformatics helps us understand complex biological problems by investigating similarities and differences that exist at sequence levels in poly-nucleic acids or proteins. The first section provides an overview of biological sequences (nucleic acids and proteins). This chapter focuses on several biological sequence analysis techniques used in computational biology and bioinformatics.