Rapid genomic sequence classification using probabilistic data structures

    公开(公告)号:US11037654B2

    公开(公告)日:2021-06-15

    申请号:US15977667

    申请日:2018-05-11

    Applicant: NOBLIS, INC.

    Abstract: Techniques for identifying and/or classifying genomic information are provided. In some embodiments, genomic information may be identified by computing systems without access to a database of reference genomic information, instead relying on locally stored probabilistic data structures representing reference genomic information. Query genomic data, such as data taken from a read-set, may be divided into sub-strings, and each of the locally-stored probabilistic data structures may be queried by each of the extracted sub-strings, generating probabilistic outputs indicating either that (a) the sub-string is probably included in the set of data represented by the probabilistic data structure or (b) the sub-string is definitely not included in the set of data. Based on the number and/or proportion of sub-strings from a read-set that are indicated as being likely represented by a probabilistic data structure, a likely identity or classification for the genomic information in the read-set may be determined.

    Data recovery through reversal of hash values using probabilistic data structures

    公开(公告)号:US11055399B2

    公开(公告)日:2021-07-06

    申请号:US16253950

    申请日:2019-01-22

    Applicant: NOBLIS, INC.

    Abstract: Systems and methods for recovering passwords from a hash value input are provided. A password space may be segmented into password sets, and a digest set may be generated for each password set. Probabilistic data structures representing the digest sets may be generated. One of the probabilistic data structures may be queried with the hash value input to determine whether the hash value input is likely included in the digest sets. In response to the hash value input being determined to be likely included in the digest set, the passwords constituting the password set corresponding to the digest set may be regenerated, and the hash values constituting the digest set may be regenerated. The generated hash values may be compared to the hash value input to determine a hash value from the digest set that matches the hash value input to recover the password associated with the matched hash value.

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