Читать книгу Data Analytics in Bioinformatics - Группа авторов - Страница 66

Classification of RNA, Protein Sequence and DNA become a challenge because of difference and similarity of many organisms.

Issue with Genome Sequence

A Genome denotes to the complete set of chromosomes of an organism consisting of DNA. Genome sequencing, is a way of mapping out DNA or ordering DNA for organizing, processing and interpreting the sequences, which again requires improvements in sequencing strategies. Each sequencing of DNA faces challenges in searching the sequence pattern, designing, analyzing and interpreting the data.

 In gene findings and genome annotation: Gene finding suggests for prediction of nucleotide sequence such as introns and exons in DNA-sequence segments, whereas genome annotation is a process of gene sequencing to find out the gene coding regions to analyze protein sequence [8]. It involves study of the repetitive DNA within the genome, emulated from either same or nearly same sequence.

 In sequence comparison: Sequence comparison is the process of comparing two or more than two sequences. Availability of large amount of sequences in genomic database requires proper categorization of DNA and protein sequence. So sequence comparison helps assigning a hypothetical structure and function to a sequence for identification, design and interpretation of sequence [8].

Analysis of sequencing or DNA sequencing is an important task because it helps to detect individual genes that are associated with a disease. When a disease affects an individual, its protein or genes get altered, that causes gene sequence alteration. So it becomes very important to detect these genes to find the cure of the disease. Traditional methods of gene detection were based on trial and error method. Now the advancement in Data mining and machine learning like Neural Network (NN) allow more precise study of genes and its sequence to simplify the task [9]. Many machine learning algorithms are used to classify the normal and abnormal genes with a great accuracy.

Solution to above problems involves following steps

 Collection of Biological Data

 Building Computational model

 Analyze and solve problems of computational model

 Test the computation algorithm

 Evaluate the performance of the model.