38 results about "Biosequence" patented technology

A method and apparatus transforms typically differing length text string representations (i.e., sequences) of biological fragments into uniform length representations. A comparison database stores a predefined number of known biological sequences. A comparison routine compares and scores a subject sequence against each known sequence in the database. Each individual score (one for each known sequence in the database) serves as a vector element forming a fixed length vector representation of the subject sequence. Vector length equals the predefined number of known biological sequences in the database. Scoring is a probability or an occurrence count of the known biological sequence in the subject sequence.

A biological data manipulation system, and a programming language and system, and a method of use thereof, are disclosed. The system, apparatus, and method include a first data file receiver for receiving a first data file having data indicative of a first data file type and data indicative of at least one biological data object, a first classifier that applies a plurality of rules to the first data file to parse the first data file into a first data file type and into a plurality of string classes, a second classifier that differentiates a master class for ones of the plurality of string classes, wherein the master class is differentiated against at least one selected from the group consisting of a single biosequence master and a multiple biosequence master, and a third classifier that classifies an at least one biological data object of the first data file, wherein the at least one biological data object is multiple inherited to the master class in accordance with at least one of the plurality of rules, and in accordance with at least a partial sequence of stored biodata compared by the third classifier against at least a partial sequence of at least one of the plurality of string classes.

The invention provides an analytic method of a biological sequence, which comprises the following steps: firstly, calculating the clearance spectrum of the biological sequence, calculating the distance between two adjacent characters in the biological sequence, and respectively calculating the occurrence frequency of the identical distance among the characters to form a clearance spectrum; secondly, calculating the similarities among different biological sequences; and thirdly deriving the homology or the biological functions of the different biological sequences. The analytic method of the biological sequences has the advantages of high speed, high sensitivity, high accuracy, and the like.

The invention relates to a database construction method and device, gene sequence association degree labeling and device, a file retrieval method and device, computer equipment and a computer readablestorage medium. According to the scheme, biological sequences and attribute information are extracted from a target file, and entries in a database are constructed based on the extracted biological sequences and attribute information; when a user performs retrieval based on the database, the server can match entries for the user through the biological sequences, the attribute information or the combination of the biological sequences and the attribute information in the entries, so that when the database is applied to a retrieval platform, various retrieval supports such as biological sequence retrieval, biological sequence attribute retrieval and comprehensive biological sequence and biological sequence attributes can be provided for users.

Systems, methods and non-transitory computer-readable media identify a candidate biological sequence for enabling a function in a host cell. Embodiments access a predictive model that associates a plurality of biological sequences, such as enzymes, with one or more functions, such as reaction catalysis; predict, using the predictive model, that one or more candidate sequences of the plurality of biological sequences enable a desired function; and classify using a processor, candidate sequences that satisfy a confidence threshold as filtered candidate sequences.

Systems, methods, and machine-readable instructions stored on machine-readable media are disclosed for receiving a first DNA sequencing result and a second DNA sequencing result, wherein the first DNA sequencing result is a result of a first DNA sequencing technique and the second DNA sequencing result is a result of a second DNA sequencing technique. A difference is determined between the first DNA sequencing result and the second DNA sequencing result. Parameters are scored corresponding to the first DNA sequencing result and to the second DNA sequencing result, wherein the scoring includes: determining a value range of a parameter in a set of reference parameters corresponding to a value of a corresponding parameter of the parameters; and assigning a score associated with the value range of the parameter in the set of reference parameters as a score of the corresponding parameter. A determination is made that the first DNA sequencing result or the second DNA sequencing result is conclusive or inconclusive based on respective scores of the parameters of the first DNA sequencing result and the second DNA sequencing result. An indication is made to perform a third DNA sequencing using a third DNA sequencing technique when the first DNA sequencing result or the second DNA sequencing result is inconclusive.

The invention provides a method for analyzing a biological sequence with a known sequence. The method comprises the following steps: (a) determining all Kmer sequences of a biological sequence on thebasis of the biological sequence, wherein the biological sequence is obtained by windowing a large-fragment amino acid sequence or nucleotide sequence; (b) determining the frequency number of each ofall the Kmer sequences, and determining at least one high-frequency Kmer and at least one low-frequency Kmer based on the frequency number; and (c) determining a preliminary repetition candidate region based on the one high-frequency Kmer, and determining whether to integrate the low-frequency Kmer into the preliminary repetition candidate region based on the distance between the low-frequency Kmer and the adjacent high-frequency Kmer.

The invention relates to a similarity analysis method of a biological sequence based on a negative sequence mode, an implementation system and a medium. The similarity analysis method comprises the following steps: (1) data preprocessing: representing letters in a DNA sequence with numbers; dividing the data into a plurality of blocks, and taking the obtained blocks as a data set for frequent pattern mining; (2) frequent pattern mining: using an fNSP algorithm to mine a data set; (3) performing graphic representation on the maximum frequent positive and negative sequence modes; converting themaximum frequent positive and negative sequence modes into a digital sequence; (4) similarity analysis of the DNA sequences: solving the similarity of different DNA sequences, and selecting the DNA sequence corresponding to the minimum similarity as the DNA sequence to be researched. According to the method, the negative sequence can be effectively expressed and analyzed, and different analysis results can be obtained by selecting different maximum frequent pattern combinations, and therefore the memory and time consumption of a computer are greatly reduced.

A similarity analysis method of negative sequential patterns based on biological sequences and its implementation system and medium comprises: (1) Data preprocessing: represent the letters in the DNA sequence with numbers; divide the sequence represented by numbers into several blocks as datasets for frequent pattern mining; (2) Frequent pattern mining: utilize the f-NSP algorithm to mine the data sets; (3) Represent the maximum frequent positive and negative sequential patterns graphically; convert the maximum frequent positive and negative sequential patterns into number sequences; (4) Similarity analysis of DNA sequence: calculate the similarity of different DNA sequences; select the DNA sequence corresponding to the minimum similarity as the sequence to be studied.