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<p><span style="font-size:14px">Bioinformatics&nbsp;is an interdisciplinary&nbsp;field that develops methods and software tools&nbsp;for understanding biological&nbsp;data. As an interdisciplinary&nbsp;field of science, bioinformatics combines computer science, statistics, mathematics, and engineering&nbsp;to analyze and interpret biological&nbsp;data. Bioinformatics has been used for in silico&nbsp;analyses of biological&nbsp;queries using mathematical&nbsp;and statistical techniques.</span></p>
<p><u><span style="font-size:14px">## Analysis ##</span></u></p>
<p><span style="font-size:14px">1) <strong>Analysis of gene expression</strong></span></p>
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<p><span style="font-size:14px">Genomics&nbsp;is a discipline in genetics&nbsp;that applies recombinant DNA, DNA sequencing&nbsp;methods, and bioinformatics&nbsp;to sequence, assemble, and analyze the function and structure of genome.&nbsp;Advances in genomics have triggered a revolution in discovery-based research to understand even the most complex biological systems such as the brain.&nbsp;The field includes efforts to determine the entire DNA sequence&nbsp;of organisms and fine-scale genetic mapping.&nbsp;The field also includes studies of intragenomic phenomena such as heterosis, epistasis, pleiotropy&nbsp;and other interactions between loci&nbsp;and alleles&nbsp;within the genome.</span><span style="font-size:11.6667px; line-height:18.6667px">&nbsp;</span><span style="font-size:14px">In contrast, the investigation of the roles and functions of single genes is a primary focus of molecular biology&nbsp;</span><span style="font-size:14px">or genetics&nbsp;</span><span style="font-size:14px">and is a common topic of modern medical and biological research. Research of single genes does not fall into the definition of genomics unless the aim of this genetic, pathway, and functional information analysis is to elucidate its effect on, place in, and response to the entire genomes networks.</span></p>
<p><span style="font-size:14px"><u>## Analysis ##</u></span></p> <h3><span style="font-size:14px">1) <strong>Sequencing</strong></span></h3> <p><span style="font-size:14px">Historically, sequencing was done in&nbsp;sequencing centers, centralized facilities (ranging from large independent institutions such as Joint Genome Institute&nbsp;which sequence dozens of terabases a year, to local molecular biology core facilities) which contain research laboratories with the costly instrumentation and technical support necessary. As sequencing technology continues to improve, however, a new generation of effective fast turnaround benchtop sequencers has come within reach of the average academic laboratory.<span style="line-height:17.3333px">&nbsp;</span>On the whole, genome sequencing approaches fall into two broad categories,&nbsp;shotgun&nbsp;and&nbsp;high-throughput&nbsp;(aka&nbsp;next-generation) sequencing.</span></p> <p><span style="font-size:14px">2) <strong>Assembly</strong></span></p> <p><span style="font-size:14px">Sequence assembly&nbsp;refers to aligning&nbsp;and merging fragments of a much longer DNA&nbsp;sequence in order to reconstruct the original sequence.&nbsp;This is needed as current DNA sequencing&nbsp;technology cannot read whole genomes as a continuous sequence, but rather reads small pieces of between 20 and 1000 bases, depending on the technology used. Typically the short fragments, called reads, result from shotgun sequencing genomic&nbsp;DNA, or gene transcripts.</span></p> <p><span style="font-size:14px">3) <strong>Annotation</strong></span></p> <p><span style="font-size:14px">The DNA sequence assembly alone is of little value without additional analysis.<span style="line-height:17.3333px">&nbsp;</span>Genome annotation&nbsp;is the process of attaching biological information to sequences,&nbsp;and consists of three main steps.&nbsp;① Identifying portions of the genome that do not code for proteins, ② Identifying elements on the genome,&nbsp;a process called gene prediction,&nbsp;and&nbsp;③ Attaching biological information to these elements.&nbsp;</span></p> <p><span style="font-size:14px">Automatic annotation tools try to perform these steps in silico,&nbsp;as opposed to manual annotation which involves human expertise and potential experimental verification.&nbsp;Ideally, these approaches co-exist and complement each other in the same annotation pipeline.&nbsp;Traditionally, the basic level of annotation is using BLAST&nbsp;for finding similarities, and then annotating genomes based on homologues.<span style="line-height:17.3333px">&nbsp;</span>More recently, additional information is added to the annotation platform. The additional information allows manual annotators to deconvolute discrepancies between genes that are given the same annotation. Some databases use genome context information, similarity scores, experimental data, and integrations of other resources to provide genome annotations through their Subsystems approach. Other databases&nbsp;rely on both curated data sources as well as a range of software tools in their automated genome annotation pipeline.&nbsp;Structural annotation&nbsp;consists of the identification of genomic elements, primarily ORFs&nbsp;and their localisation, or gene structure.&nbsp;Functional&nbsp;annotation&nbsp;consists of attaching biological information to genomic elements.</span></p> <p>&nbsp;</p> <p><span style="font-size:20px">TRANSCRIPTOMICS&nbsp;</span></p>
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