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Bloom Filters In Bioinformatics
Bloom filters are space-efficient probabilistic data structures used to test whether an element is a part of a set. Bloom filters require much less space than other data structures for representing sets, however the downside of Bloom filters is that there is a false positive rate when querying the data structure. Since multiple elements may have the same hash values for a number of hash functions, then there is a probability that querying for a non-existent element may return a positive if another element with the same hash values has been added to the Bloom filter. Assuming that the hash function has equal probability of selecting any index of the Bloom filter, the false positive rate of querying a Bloom filter is a function of the number of bits, number of hash functions and number of elements of the Bloom filter. This allows the user to manage the risk of a getting a false positive by compromising on the space benefits of the Bloom filter. Bloom filters are primarily used in bioin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bloom Filter
A Bloom filter is a space-efficient probabilistic data structure, conceived by Burton Howard Bloom in 1970, that is used to test whether an element is a member of a set. False positive matches are possible, but false negatives are not – in other words, a query returns either "possibly in set" or "definitely not in set". Elements can be added to the set, but not removed (though this can be addressed with the counting Bloom filter variant); the more items added, the larger the probability of false positives. Bloom proposed the technique for applications where the amount of source data would require an impractically large amount of memory if "conventional" error-free hashing techniques were applied. He gave the example of a hyphenation algorithm for a dictionary of 500,000 words, out of which 90% follow simple hyphenation rules, but the remaining 10% require expensive disk accesses to retrieve specific hyphenation patterns. With sufficient core memory, an error-free hash coul ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
BLAST (biotechnology)
In bioinformatics, BLAST (basic local alignment search tool) is an algorithm and program for comparing primary biological sequence information, such as the amino-acid sequences of proteins or the nucleotides of DNA and/or RNA sequences. A BLAST search enables a researcher to compare a subject protein or nucleotide sequence (called a query) with a library or database of sequences, and identify database sequences that resemble alphabet above a certain threshold. For example, following the discovery of a previously unknown gene in the mouse, a scientist will typically perform a BLAST search of the human genome to see if humans carry a similar gene; BLAST will identify sequences in the pig genome that resemble the mouse gene based on similarity of sequence. Background BLAST, which ''The New York Times'' called ''the Google of biological research'', is one of the most widely used bioinformatics programs for sequence searching. It addresses a fundamental problem in bioinformatics r ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Next-generation Sequencing
Massive parallel sequencing or massively parallel sequencing is any of several high-throughput approaches to DNA sequencing using the concept of massively parallel processing; it is also called next-generation sequencing (NGS) or second-generation sequencing. Some of these technologies emerged between 1994 and 1998 and have been commercially available since 2005. These technologies use miniaturized and parallelized platforms for sequencing of 1 million to 43 billion short reads (50 to 400 bases each) per instrument run. Many NGS platforms differ in engineering configurations and sequencing chemistry. They share the technical paradigm of massive parallel sequencing via spatially separated, clonally amplified DNA templates or single DNA molecules in a flow cytometry, flow cell. This design is very different from that of Sanger sequencing—also known as capillary sequencing or first-generation sequencing—which is based on electrophoretic separation of chain-termination products produ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
De Bruijn Graph
In graph theory, an -dimensional De Bruijn graph of symbols is a directed graph representing overlaps between sequences of symbols. It has vertices, consisting of all possible sequences of the given symbols; the same symbol may appear multiple times in a sequence. For a set of symbols the set of vertices is: :V=S^n=\. If one of the vertices can be expressed as another vertex by shifting all its symbols by one place to the left and adding a new symbol at the end of this vertex, then the latter has a directed edge to the former vertex. Thus the set of arcs (that is, directed edges) is :E=\. Although De Bruijn graphs are named after Nicolaas Govert de Bruijn, they were discovered independently by both De Bruijn and I. J. Good. Much earlier, Camille Flye Sainte-Marie implicitly used their properties. Properties * If , then the condition for any two vertices forming an edge holds vacuously, and hence all the vertices are connected, forming a total of edges. * Each vertex has ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Genome Assembly
In bioinformatics, sequence assembly refers to aligning and merging fragments from a longer DNA sequence in order to reconstruct the original sequence. This is needed as DNA sequencing technology might not be able to 'read' whole genomes in one go, but rather reads small pieces of between 20 and 30,000 bases, depending on the technology used. Typically, the short fragments (reads) result from shotgun sequencing genomic DNA, or gene transcript ( ESTs). The problem of sequence assembly can be compared to taking many copies of a book, passing each of them through a shredder with a different cutter, and piecing the text of the book back together just by looking at the shredded pieces. Besides the obvious difficulty of this task, there are some extra practical issues: the original may have many repeated paragraphs, and some shreds may be modified during shredding to have typos. Excerpts from another book may also be added in, and some shreds may be completely unrecognizable. Gen ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Comparing De Brujin Graph In Memory
Comparison or comparing is the act of evaluating two or more things by determining the relevant, comparable characteristics of each thing, and then determining which characteristics of each are similar to the other, which are different, and to what degree. Where characteristics are different, the differences may then be evaluated to determine which thing is best suited for a particular purpose. The description of similarities and differences found between the two things is also called a comparison. Comparison can take many distinct forms, varying by field: To compare things, they must have characteristics that are similar enough in relevant ways to merit comparison. If two things are too different to compare in a useful way, an attempt to compare them is colloquially referred to in English as "comparing apples and oranges." Comparison is widely used in society, in science and in the arts. General usage Comparison is a natural activity, which even animals engage in when dec ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
