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I strongly suggest you to take a free course on courseraThere are many valid courses focused on bioinformatics for beginners and they offers slides, notes and everything is necessary to start. If you are looking for a nice book to get started, then I suggest you this one


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While not a book per se, the edX Lifesciences course has been really useful for me, it does a great job of covering the entire pipeline of genome analysis that one would need to use. The link containing all 8 classes is here, scroll down a bit and you can see links to all of the classes in this module: ...


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Elementary Sequence Analysis by Brian Golding and Dick Morton is a good starter. Online resources can be found here:http://helix.biology.mcmaster.ca/courses.html Here's a great online tutorial for sequencing techniques, with introduction, examples and everything. http://bioinf.comav.upv.es/courses/sequence_analysis/sequencing_technologies.html


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Unix and Perl to the Rescue by Keith Bradnam and Ian Korf is an excellent introductory book and guide for bioinformatics (Linux and Perl) in genomics. It includes exercises and starts with the very fundamentals. You will still need some basic understanding of genetics and biology though.


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Beginning Perl for Bioinformatics by Jim Tisdall http://shop.oreilly.com is quite good, in my opinion, and his sequel, Mastering Perl for Bioinformatics is also great. The focus is largely, but not exclusively genomics.


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A 'good' phylogenetic tree would be completely refined, properly binary, have high bootstrap support for all its branches, and reconstruct clades we think exist with high support values. Generally high support values(there are other methods besides bootstrapping but that is a question for another time) is a measure of a good tree. There are other concerns, ...


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It means incomplete separation or a failure to split into two groups unambiguously. There are multiple ways to estimate the resolution of a phylogenetic tree; involving an index to measure the likelihood of observing the phylogenetic tree that you derive relative to those produced by drawing species at random, for instance, or permuting species to produce ...


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take the gene names and copy all of them, next open an online tool called gene mania. paste all your genes on the window. you will get their interaction and other related genes. Now go to a database called gene cards and type in all the gene you got from gene mania and paste it one after the other to get useful information about the individual genes. some of ...


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Reference genomes do not accurately represent the set of genes of any single person.it is created by fragments of various donors, which when built,is used as a template for creating the real genome. Though we will find All humans are 99.9 per cent identical and, of that tiny 0.1 per cent difference the reference genome might not be 100% identical to the real ...


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The main reason is because the genetic differences between individuals of the same species are tiny. For the vast majority of studies, they can simply be ignored. Differences between individuals are usually (not always, but mostly) differences in SNP genotypes. These are single nucleotide differences which, while they can have phenotypic effect, don't ...


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Evolution Evolution is the accumulation of genetic mutations that results in phenotypic variation (physical characteristics) where surviving variations are more suited to the environment the organism lives in, thus allowing it to survive better and -- critically -- reproduce as-good-as or better-than its competing organisms. In terms of computer ...


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Please note that these are just analogies not exact definitions. Okay so let's imagine DNA as string of 4 letters that is the program code of an organism. Also the running environment is a good analogue to the biological environment (RAM, CPU time, disk space - as resources like food, water etc.) Genes of organism could be imagined as methods of an object ...


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Also try putting the list through Reactome or String DB to see if you see mapping to certain pathways. http://string-db.org/ You can also put lists through ConceptGen to carry out ontology based analyses http://portal.ncibi.org/gateway/conceptgen.html


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Question 1: The phenomena you describe in which it matters whether you have one or two copies of an allele (e.g., the AA phenotype being different than the Aa phenotype) are known as dominance effects. Dominance effects can interact with epistatic effects (in which the phenotypic effect of one locus depends on the genotype at the another locus). One good ...


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Was getting long in the comments. In light of your comments, you might be interested in Gene-set enrichment analysis (GSEA). You can do a GSEA using your set, the other one coming from reference databases such as MSigDB (see here). You can categorize your list by gene families using this technique for example. You can get an idea of what cellular process ...


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There are some databases in which you can search for E.coli gene expression data: GenExpDB: E. coli Gene Expression Database Many Microbe Microarrays Database (M3D): A resource of microbial gene expression data Stanford MicroArray Database (use the search tool to find relevant organisms) Colombos (COLlection Of Microarrays for Bacterial OrganismS) ...


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It depends; what species are the genes from? Some organisms have extensively annotated genomes, and actively curated species-specific databases, while other species may not even have a reference genome sequence available. By itself, a priori, if you were lucky, about all you list would tell you was how to spell the names of those genes--if you're lucky. But ...


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I would suggest searching the name in any trusted genetics database such as NCBI's GenBank (http://www.ncbi.nlm.nih.gov/genbank/). You can just Google search it, but it may take a little longer to find useful information that way. I hope this helps and good luck with your research, CDB


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Proteins evolve and have different sequences between species, so you would have to define what you mean with "same protein". One option would be to use an orthology database like eggNOG. (eggNOG has the same protein identifiers as STRING.) Then you could figure out 1:1 correspondences between proteins. You probably also want to read up on Roded Sharan's ...


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If I understand it correctly you have downloaded for example 1000 protein sequences with 1000 IDs, but there are duplicates in sequences so in reality it is like having 600 unique sequences with 1000 ID's? If so it should be fairly easy to write a script which would create a set of unique sequences with all corresponding IDs so you could choose which one to ...



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