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The BLAST algorithm was produced by Altschul, Gish, Miller, around 1990 at the National Center for Biotechnology Information (NCBI). BLAST is used to derive functional and evolutionary relationships among sequences and to help recognize members of gene families.The NCBI website includes several common BLAST databases. As per their content, they are combined into nucleotide and protein databases. NCBI also supports specialized BLAST databases including the vector screening database, there are several genome databases for multiple organisms, and trace databases.BLAST uses a heuristic approaches to discover the largest local alignments between a query sequence and a database. BLAST increase the complete ... Read More
To return a copy of an array with the leading characters removed, use the numpy.char.lstrip() method in Python Numpy. The "chars" parameter is used to set a string specifying the set of characters to be removed. If omitted or None, the chars argument defaults to removing whitespace. The chars argument is not a prefix; rather, all combinations of its values are stripped.The numpy.char module provides a set of vectorized string operations for arrays of type numpy.str_ or numpy.bytes_.The chars parameter is a string specifying the set of characters to be removed. If omitted or None, the chars argument defaults to ... Read More
The alignment depends on the fact that all living organisms are associated by evolution. This uses that the nucleotide (DNA, RNA) and proteins series of the species that are nearer to each other in evolution must exhibit higher similarities.An alignment is the phase of lining up sequences to obtain a maximal level of identity, which also defines the degree of similarity among sequences. There are two sequences are homologous if they send a common ancestor.The degree of similarity acquired by sequence alignment can be beneficial in deciding the possibility of homology among two sequences. Such an alignment support decide the ... Read More
To multiply each element of a masked Array by a scalar value in-place, use the ma.MaskedArray.__imul__() method in Python Numpy. A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. It supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and ... Read More
GSP stands for Generalised Sequential Patterns. It is a sequential pattern mining method that was produced by Srikant and Agrawal in 1996. It is an expansion of their seminal algorithm for usual itemset mining, referred to as Apriori. GSP needs the downward-closure natures of sequential patterns and adopts a several-pass, students create-and-test approach.The algorithm is as follows. In the first scan of the database, it can discover some frequent items, i.e., those with minimum support. Each item yields a 1-event frequent sequence including that item. Each subsequent pass begins with a seed group of sequential patterns and the group of ... Read More
To subtract a scalar value from each element of a masked Array in-place, use the ma.MaskedArray.__isub__() method in Python Numpy.A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. It supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse ... Read More
To compute the bit-wise NOT of an array element-wise, use the numpy.bitwise_not() method in Python Numpy. Computes the bit-wise NOT of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator ˜.The where parameter is the condition broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default out=None, locations within it where the condition is False will remain uninitialized.StepsAt first, import ... Read More
Sequential pattern mining is the mining of frequently appearing series events or subsequences as patterns. An instance of a sequential pattern is users who purchase a Canon digital camera are to purchase an HP color printer within a month.For retail information, sequential patterns are beneficial for shelf placement and promotions. This industry, and telecommunications and different businesses, can also use sequential patterns for targeted marketing, user retention, and several tasks.There are several areas in which sequential patterns can be used such as Web access pattern analysis, weather prediction, production processes, and web intrusion detection.Given a set of sequences, where each ... Read More
To return a copy of an array with the leading spaces removed, use the numpy.char.lstrip() method in Python Numpy. The function returns an output array of str or unicode, depending on input type.The numpy.char module provides a set of vectorized string operations for arrays of type numpy.str_ or numpy.bytes_.The chars parameter is a string specifying the set of characters to be removed. If omitted or None, the chars argument defaults to removing whitespace. The chars argument is not a prefix; rather, all combinations of its values are stripped.StepsAt first, import the required library −import numpy as npCreate a One-Dimensional array ... Read More
STREAM is an individual-pass, constant element approximation algorithm that was produced for the k-medians problem. The k-medians problem is to cluster N data points into k clusters or groups such that the sum squared error (SSQ) between the points and the cluster center to which they are assigned is minimized. The idea is to assign similar points to the same cluster, where these points are dissimilar from points in other clusters.In the stream data model, data points can only be seen once, and memory and time are limited. It can implement high-quality clustering, the STREAM algorithm processes data streams in ... Read More