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1 mportant tasks in biomedical text mining and information retrieval.
2 uccessful in large optimization problems for information retrieval.
3 classification is proposed to aid biomedical information retrieval.
4 DCG), a common measure for the usefulness of information retrieval.
5 -gene bioactivity prediction, and biomedical information retrieval.
6 comprehend form and to facilitate convenient information retrieval.
7 y and difficult process and assuring optimal information retrieval.
8 t was induced selectively by an influence on information retrieval.
9 ity, robust security, and accurate and rapid information retrieval.
10 are critical for efficient data analysis and information retrieval.
11 asks, providing transparent, domain-specific information retrieval.
12 l and cost-efficient solution for biomedical information retrieval, achieving substantial performance
13  output formats and the tasks they fulfil in information-retrieval activities.
14  part of the Gene Ontology database into our information retrieval algorithms to broaden the coverage
15                      Our system also applies information retrieval algorithms to discover knowledge o
16 e is a need for a comprehensive database and information retrieval and analysis system that will prov
17  machine learning, computational statistics, information retrieval and data science.
18  to quality patient care rounds include poor information retrieval and documentation, interruptions,
19 ne of the known names for a gene or protein, information retrieval and extraction would benefit from
20 rs indexing algorithms and adversely affects information retrieval and extraction.
21  data mining and sequence analysis tools for information retrieval and functional identification of p
22 s have proposed a large number of biological information retrieval and knowledge acquisition methods.
23 a analysis tools to underlying databases for information retrieval and knowledge discovery, with func
24                             The authors used information retrieval and natural language processing me
25 y facilitates the applications of biomedical information retrieval and text mining.
26 direct on-line sequence similarity searches, information retrieval, and knowledge discovery by provid
27                      Using an alignment-free information-retrieval approach, we have comprehensively
28 ere we present a two-stage machine learning, information retrieval, approach to fold recognition.
29  to support the unbiased evaluation of novel information retrieval approaches.
30 eloped for protein family identification and information retrieval, as an approach to undertake the h
31 oncology audience, as this may help ease the information retrieval burden facing participants in the
32 lated to the well-known average precision in information retrieval, but reflecting the usage of E-val
33 e effectiveness and efficiency of biomedical information retrieval by proposing ranking-based methods
34                            This challenge of information retrieval can be characterized in terms of "
35 statistically and clinically significant for information retrieval, disease diagnosis and prognosis.
36  probabilistic query method enables reliable information retrieval even though the gene-cell-type ass
37 determine which obtained the best results in information retrieval exercises.
38 een introduced to measure the performance of information retrieval for biomedical applications.
39 l PFC plays a differentially greater role in information retrieval for slower subjects, possibly beca
40 re, we propose criteria that ensure complete information retrieval for the DNA origami cryptography.
41 sions that require accurate, domain-specific information retrieval from complex tobacco industry docu
42                             RAG incorporates information retrieval from external sources to supplemen
43 ted DNA and/or protein sequences, as well as information retrieval, have become increasingly difficul
44 cy and the computation of other metrics from information retrieval, here specialized for biological s
45 mprehensive quality controls, and biological information retrieval in large volumes of genomic data.
46 ave examined existing web-based services for information retrieval in order to give users guidance to
47 ential to aid in efficient data analysis and information retrieval in the field of biomedical researc
48 g techniques, which involve the processes of information retrieval, information extraction and data m
49         One of the challenges in large-scale information retrieval (IR) is developing fine-grained an
50                                              Information retrieval (IR) is essential in biomedical kn
51      Despite the proliferation of electronic information retrieval (IR) systems for physicians, their
52 e general Web search engines and specialized information retrieval (IR) systems have made important s
53 y significant improvement can be obtained in information retrieval (IR) when the text of a user's que
54 n, where the effective and secure healthcare information retrieval is complex.
55 bute to overcoming the streetlight effect in information retrieval, making up the key components of K
56 e profiles to the disambiguation task via an information retrieval method, which ranks the similarity
57                                 We developed information retrieval methodologies to search over 200 m
58 een a challenging task in the field of Music Information Retrieval (MIR) due to the intricate and div
59 es and low-level features derived from Music Information Retrieval (MIR).
60                                          The information retrieval module currently retrieves informa
61          The model, called simplified memory information retrieval network (SMIRN), is a bi-modular h
62 es: the ProteinInfo program from the Protein information Retrieval On-line World Wide Web Lab or PROW
63 mposed of four modules: gene set management, information retrieval, organization/visualization, and s
64 were most commonly associated with errors in information retrieval, particularly with recent publicat
65                                      From an information retrieval perspective, normalization facilit
66             We combined several metrics from information retrieval popular in the literature: mean pr
67                    By considering this as an information retrieval problem, we have adapted methods d
68   Previous coordination with other units and information retrieval regarding patient and relatives' s
69 res with NOESY peak lists using methods from information retrieval statistics.
70 h methods for hit-specific and data set-wide information retrieval, suited to any genome-based analyt
71 ignments, and links to the Entrez integrated information retrieval system at the National Center for
72                                    The ATLAS information retrieval system can be used to browse and q
73 problems are addressed by KiPar, a dedicated information retrieval system designed to facilitate acce
74                              We introduce an information retrieval system for large metagenomic data
75                                    An online information retrieval system was designed to ensure the
76 ing air pollution values from the Aerometric Information Retrieval System with the patients' home zip
77 d into the National Center for Biotechnology Information retrieval system, making them searchable by
78 e alignments, links to the Entrez integrated information retrieval system, structures for histone and
79 say data are integrated into the NCBI Entrez information retrieval system, thus making PubChem data s
80 formation easily accessible through the NCBI information retrieval system-Entrez, and various web-bas
81            Indexing is a crucial step in any information retrieval system.
82 improvements in the functionality of the CDD information retrieval system.
83 recorded and analyzed using a computer-based information retrieval system.
84 be exploited to improve the effectiveness of information retrieval systems.
85 ental computing problem faced by large-scale information retrieval systems.
86                            The evaluation of information retrieval techniques has traditionally relie
87 ribe two protocols for evaluating biomedical information retrieval techniques without human relevance
88 common approach to this goal has been to use information retrieval technology to improve access to te
89 peptide searches facilitates speedy, dynamic information retrieval that may significantly benefit cli
90                           To maximize family information retrieval, the database provides links to va
91                           To maximize family information retrieval, the database provides links to va
92 adapted from natural language processing and information retrieval to cluster and organize these feat
93 r, in many fundamental problems ranging from information retrieval to drug discovery, only the very t
94 tic Indexing (LSI), a vector space model for information retrieval, to automatically identify concept
95                                   To improve information retrieval, we leverage the structure of the
96                     Multiple techniques from information retrieval were used to preprocess the functi