About: Efficient Database Search via Tensor Distribution Bucketing

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Efficient Database Search via Tensor Distribution Bucketing
Creator	Davoodi, Arash Mohimani, Hosein Mongia, Mihir Soudry, Benjamin
Source	PMC
abstract	In mass spectrometry-based proteomics, one needs to search billions of mass spectra against the human proteome with billions of amino acids, where many of the amino acids go through post-translational modifications. In order to account for novel modifications, we need to search all the spectra against all the peptides using a joint probabilistic model that can be learned from training data. Assuming M spectra and N possible peptides, currently the state of the art search methods have runtime of O(MN). Here, we propose a novel bucketing method that sends pairs with high likelihood under the joint probabilistic model to the same bucket with higher probability than those pairs with low likelihood. We demonstrate that the runtime of this method grows sub-linearly with the data size, and our results show that our method is orders of magnitude faster than methods from the locality sensitive hashing literature. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this chapter (10.1007/978-3-030-47436-2_26) contains supplementary material, which is available to authorized users.
has issue date	2020-04-17(xsd:dateTime)
bibo:doi	10.1007/978-3-030-47436-2_26
has license	no-cc
sha1sum (hex)	2313bc846086535eb7501f444512a82ba244973d
schema:url	https://doi.org/10.1007/978-3-030-47436-2_26
resource representing a document's title	Efficient Database Search via Tensor Distribution Bucketing
has PubMed Central identifier	PMC7206332
schema:publication	Advances in Knowledge Discovery and Data Mining
resource representing a document's body	covid:2313bc846086535eb7501f444512a82ba244973d#body_text
is schema:about of	named entity 'grows' named entity 'probabilistic model' named entity 'probability' named entity 'TRAINING' named entity 'LIKELIHOOD' named entity 'PROBABILITY' named entity 'CURRENTLY' named entity 'ORDERS' named entity 'LOCALITY' named entity 'PEPTIDES' named entity 'MAGNITUDE' covid:arg/2313bc846086535eb7501f444512a82ba244973d named entity 'bucketing' named entity 'peptides' named entity 'orders' named entity 'sends' named entity 'probabilistic model' named entity 'amino acids' named entity 'mass spectrometry' named entity 'bucketing method' named entity 'posttranslational modifications' named entity 'probability' named entity '95%' named entity 'algorithm' named entity 'proteomics' named entity 'algorithm' named entity 'Algorithm' named entity 'asymptotic complexity' named entity 'nearest neighbor search' named entity 'joint distribution' named entity 'high-dimensional data' named entity 'search problem' named entity 'search problem' named entity 'probability' named entity 'vector' named entity 'hashes' named entity 'probability distribution' named entity 'Algorithm' named entity 'hash table' named entity 'data points' named entity 'bucketing method' named entity 'probability' named entity 'previous section' named entity 'locality sensitive hashing' named entity 'mass spectrometry' named entity 'vectors' named entity 'MIPS' named entity 'cell culture' named entity 'Algorithm' named entity 'True Positive Rate' named entity 'euclidean distance' named entity 'matrices' named entity 'algorithm' named entity 'Bucketing' named entity 'probability distribution' named entity 'vector' named entity 'proteomics' named entity 'data point' named entity 'uth' named entity 'mass spectrum' named entity 'discretized' named entity 'integer linear programming' named entity 'previous section' named entity 'algorithm' named entity 'Locality Sensitive Hashing' named entity 'mass spectra' named entity 'locality sensitive hashing' named entity 'nearest neighbor search' named entity 'hamming distance' named entity 'hash functions' named entity 'probability distributions' named entity 'Bucketing' named entity 'hashed' named entity 'ANN' named entity 'Algorithm' named entity 'mass-spectrometry' named entity 'minimization problem' named entity 'search problem' named entity 'data points' named entity 'algorithm'

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