By David D. Womble (auth.), Stephen Misener, Stephen A. Krawetz (eds.)
In Bioinformatics: equipment and Protocols, hands-on clients and specialists survey the foremost organic software program programs, supplying necessary assistance and an outline of present advancements. one of the series research platforms reviewed are GCG, Omiga, MacVector, DNASTAR, PepTool, GeneTool, and Staden. Molecular biology software program comprises Genotator and sequence-similarity looking utilizing FASTA, CLUSTAL a number of series alignment, and phylogenic research. Web-based assets are tested for basic series databases, basic series research tools, and medical databases beneficial in molecular medication. The ebook additionally features a set of directions for designing and educating an introductory bioinformatics direction and diverse illustrative examples to coach the reader tips to remedy difficulties.
Bioinformatics: equipment and Protocols bargains to skilled and amateur biologists a extensive evaluation of the computational instruments that experience reshaped smooth biology. It constitutes a gold-standard reference for latest scientists who desire to increase and hone their bioinformatics talents in the direction of the invention of recent organic relationships.
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Extra info for Bioinformatics Methods and Protocols
Minimum memory required is 4 mb of RAM, though at least 6 mb of RAM is recommended. Connection to the Internet is· required for access to the NCBI databases. For greatest utility a color monitor and a Macintosh-compatible printer are also recommended. The From: Me117ods in Molecular Biology. vol. 132: Bioinformatics Methods and ProtocOls Edited by: s. Misener and S. A. 5CD. Being a commercial program, Mac Vector is copy protected. The copy pro~ tection can either be via hardware or software. The hardware copy-protection device is called the EvE key, which connects to the Macintosh' s Apple Desktop Bus (ADB).
Imported sequences arc converted to the Omiga format The Omiga format includes any additional features and information that was in the original sequence file, such as coding regions, transcription start sites, termination codons, polyadenylation signals, and so on. Upon importing new sequences, many such features may be identified based on primary sequence data alone. However, it is often both useful and timely to have these items already identified. Further, many of the features identified in GenBank sequences, for example, are based not on primary sequence data but rather on experimental data.
The sequence view can be used to edit a sequence by hand. This feature can be used to reflect site-specific mutations introduced into the sequence in the laboratory as well as sequence polymorphisms. The edited sequence can then be used to identify new restriction sites generated by the specific alterations. Editing can also be used to add a large piece of one sequence to another sequence to reflect cloning experiments in the laboratory. Thus, an experiment involving the cloning of an insert isolated from a library 1nto a plasmid vector can be simulated us1ng Omiga, provided the sequence of the vector and the insert arc known.