The Feature Description of Formal Context Based on the Relationships among Concept Lattices.
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ABSTRACT:
SUBMITTER: Qian T
PROVIDER: S-EPMC8625367 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Rule acquisition is one of the main purposes in the analysis of formal decision contexts. Up to now, there have been several types of rules in formal decision contexts such as decision rules, decision implications, and granular rules, which can be viewed as ∧-rules since all of them have the following form: "if conditions 1,2,…, and m hold, then decisions hold." In order to enrich the existing rule acquisition theory in formal decision contexts, this study puts forward two new types of rules which are called ∨-rules and ∨-∧ mixed rules based on formal, object-oriented, and property-oriented concept lattices. Moreover, a comparison of ∨-rules, ∨-∧ mixed rules, and ∧-rules is made from the perspectives of inclusion and inference relationships. Finally, some real examples and numerical experiments are conducted to compare the proposed rule acquisition algorithms with the existing one in terms of the running efficiency.
| S-EPMC4137553 | biostudies-other
Project description:Three-way concept analysis is a newly proposed area of formal concept analysis from which one can obtain both the inclusion decision and the exclusion decision. In general, given a context, some attributes may not be essential in three-way concept analysis, such as forming three-way concept lattice. So in this paper, we study the attribute reductions of three-way concept lattices in order to make the data easily be understood. Firstly, based on different criteria generated from object-induced three-way concept (OE-concept), four kinds of attribute reductions are proposed. The four reductions together embody different characteristics of a formal context and can be used in different occasions. Secondly, we discuss their relationships, including their advantages and disadvantages and the relationships among consistent sets and among the cores. Thirdly, based on attribute-induced three-way concept (AE-concept), we also give four attribute-induced three-way attribute reductions and discuss their relationships. Finally, the approaches to computing these attribute reductions are presented and the obtained results are demonstrated and verified by an empirical case. In this paper, we systematically investigate the attribute reductions of three-way concept lattices which enriches the study of formal concept analysis.
| S-EPMC7126604 | biostudies-literature
Project description:BackgroundAs biomedical knowledge is rapidly evolving, concept enrichment of biomedical terminologies is an active research area involving automatic identification of missing or new concepts. Previously, we prototyped a lexical-based formal concept analysis (FCA) approach in which concepts were derived by intersecting bags of words, to identify potentially missing concepts in the National Cancer Institute (NCI) Thesaurus. However, this prototype did not handle concept naming and positioning. In this paper, we introduce a sequenced-based FCA approach to identify potentially missing concepts, supporting concept naming and positioning.MethodsWe consider the concept name sequences as FCA attributes to construct the formal context. The concept-forming process is performed by computing the longest common substrings of concept name sequences. After new concepts are formalized, we further predict their potential positions in the original hierarchy by identifying their supertypes and subtypes from original concepts. Automated validation via external terminologies in the Unified Medical Language System (UMLS) and biomedical literature in PubMed is performed to evaluate the effectiveness of our approach.ResultsWe applied our sequenced-based FCA approach to all the sub-hierarchies under Disease or Disorder in the NCI Thesaurus (19.08d version) and five sub-hierarchies under Clinical Finding and Procedure in the SNOMED CT (US Edition, March 2020 release). In total, 1397 potentially missing concepts were identified in the NCI Thesaurus and 7223 in the SNOMED CT. For NCI Thesaurus, 85 potentially missing concepts were found in external terminologies and 315 of the remaining 1312 appeared in biomedical literature. For SNOMED CT, 576 were found in external terminologies and 1159 out of the remaining 6647 were found in biomedical literature.ConclusionOur sequence-based FCA approach has shown the promise for identifying potentially missing concepts in biomedical terminologies.
| S-EPMC8579614 | biostudies-literature
Project description:MotivationIn the available databases, biological processes are described from molecular and cellular points of view, but these descriptions are represented with text annotations that make it difficult to handle them for computation. Consequently, there is an obvious need for formal descriptions of biological processes.ResultsWe present a formalism that uses the BioPsi concepts to model biological processes from molecular details to networks. This computational approach, based on elementary bricks of actions, allows us to calculate on biological functions (e.g. process comparison, mapping structure-function relationships, etc.). We illustrate its application with two examples: the functional comparison of proteases and the functional description of the glycolysis network. This computational approach is compatible with detailed biological knowledge and can be applied to different kinds of systems of simulation.Availabilitywww.sysdiag.cnrs.fr/publications/supplementary-materials/BioPsi_Manager/.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC2881354 | biostudies-literature
Project description:There is urgent need for a formal nomenclature of sequence-based, voucherless Fungi, given that environmental sequencing has accumulated more than one billion fungal ITS reads in the Sequence Read Archive, about 1,000 times as many as fungal ITS sequences in GenBank. These unnamed Fungi could help to bridge the gap between 115,000 to 140,000 currently accepted and 2.2 to 3.8 million predicted species, a gap that cannot realistically be filled using specimen or culture-based inventories. The Code never aimed at placing restrictions on the nature of characters chosen for taxonomy, and the requirement for physical types is now becoming a constraint on the advancement of science. We elaborate on the promises and pitfalls of sequence-based nomenclature and provide potential solutions to major concerns of the mycological community. Types of sequence-based taxa, which by default lack a physical specimen or culture, could be designated in four alternative ways: (1) the underlying sample ('bag' type), (2) the DNA extract, (3) fluorescent in situ hybridization (FISH), or (4) the type sequence itself. Only (4) would require changes to the Code and the latter would be the most straightforward approach, complying with three of the five principal functions of types better than physical specimens. A fifth way, representation of the sequence in an illustration, has been ruled as unacceptable in the Code. Potential flaws in sequence data are analogous to flaws in physical types, and artifacts are manageable if a stringent analytical approach is applied. Conceptual errors such as homoplasy, intragenomic variation, gene duplication, hybridization, and horizontal gene transfer, apply to all molecular approaches and cannot be used as a specific argument against sequence-based nomenclature. The potential impact of these phenomena is manageable, as phylogenetic species delimitation has worked satisfactorily in Fungi. The most serious shortcoming of sequence-based nomenclature is the likelihood of parallel classifications, either by describing taxa that already have names based on physical types, or by using different markers to delimit species within the same lineage. The probability of inadvertently establishing sequence-based species that have names available is between 20.4 % and 1.5 % depending on the number of globally predicted fungal species. This compares favourably to a historical error rate of about 30 % based on physical types, and this rate could be reduced to practically zero by adding specific provisions to this approach in the Code. To avoid parallel classifications based on different markers, sequence-based nomenclature should be limited to a single marker, preferably the fungal ITS barcoding marker; this is possible since sequence-based nomenclature does not aim at accurate species delimitation but at naming lineages to generate a reference database, independent of whether these lineages represent species, closely related species complexes, or infraspecies. We argue that clustering methods are inappropriate for sequence-based nomenclature; this approach must instead use phylogenetic methods based on multiple alignments, combined with quantitative species recognition methods. We outline strategies to obtain higher-level phylogenies for ITS-based, voucherless species, including phylogenetic binning, 'hijacking' species delimitation methods, and temporal banding. We conclude that voucherless, sequence-based nomenclature is not a threat to specimen and culture-based fungal taxonomy, but a complementary approach capable of substantially closing the gap between known and predicted fungal diversity, an approach that requires careful work and high skill levels.
| S-EPMC6048566 | biostudies-literature
Project description:Formal concept analysis has been largely applied to explore taxonomic relationships and derive ontologies from text collections. Despite its recognized relevance, it generally misses relevant concept associations and suffers from the need to learn from Boolean space models. Biclustering, the discovery of coherent concept associations (subsets of documents correlated on subsets of terms and topics), is here suggested to address the aforementioned problems. This work proposes a structured view on why, when and how to apply biclustering for concept analysis, a subject remaining largely unexplored up to date. Gathered results from a large text collection confirm the relevance of biclustering to find less-trivial, yet actionable and statistically significant concept associations.
| S-EPMC7148255 | biostudies-literature
Project description:Identifying reliable domain-domain interactions will increase our ability to predict novel protein-protein interactions, to unravel interactions in protein complexes, and thus gain more information about the function and behavior of genes. One of the challenges of identifying reliable domain-domain interactions is domain promiscuity. Promiscuous domains are domains that can occur in many domain architectures and are therefore found in many proteins. This becomes a problem for a method where the score of a domain-pair is the ratio between observed and expected frequencies because the protein-protein interaction network is sparse. As such, many protein-pairs will be non-interacting and domain-pairs with promiscuous domains will be penalized. This domain promiscuity challenge to the problem of inferring reliable domain-domain interactions from protein-protein interactions has been recognized, and a number of work-arounds have been proposed. This paper reports on an application of Formal Concept Analysis to this problem. It is found that the relationship between formal concepts provides a natural way for rare domains to elevate the rank of promiscuous domain-pairs and enrich highly ranked domain-pairs with reliable domain-domain interactions. This piggybacking of promiscuous domain-pairs onto less promiscuous domain-pairs is possible only with concept lattices whose attribute-labels are not reduced and is enhanced by the presence of proteins that comprise both promiscuous and rare domains.
| S-EPMC3929762 | biostudies-literature
Project description:'Othering' is described as a social process whereby a dominant group or person uses negative attributes to define and subordinate others. Literature suggests othering creates exclusive relationships and puts patients at risk for suboptimal care. A concept analysis delineating the properties of othering was conducted to develop knowledge to support inclusionary practices in nursing.Rodgers' Evolutionary Method for concept analysis guided this study.The following databases were searched spanning the years 1999-2015: CINAHL, PUBMED, PsychINFO and Google. Search terms included "othering", "nurse", "other", "exclusion" and "patient".Twenty-eight papers were analyzed whereby definitions, related concepts and othering attributes were identified. Findings support that othering in nursing is a sequential process with a trajectory aimed at marginalization and exclusion, which in turn has a negative impact on patient care and professional relationships. Implications are discussed in terms of deriving practical solutions to disrupt othering. We conclude with a conceptual foundation designed to support inclusionary strategies in nursing.
| S-EPMC5500989 | biostudies-other
Project description:An implicational base is knowledge extracted from a formal context. The implicational base of a formal context consists of attribute implications which are sound, complete, and non-redundant regarding to the formal context. Non-redundant means that each attribute implication in the implication base cannot be inferred from the others. However, sometimes some attribute implications in the implication base can be inferred from the others together with a prior knowledge. Regarding knowledge discovery, such attribute implications should be not considered as new knowledge and ignored from the implicational base. In other words, such attribute implications are redundant based on prior knowledge. One sort of prior knowledge is a set of constraints that restricts some attributes in data. In formal context, constraints restrict some attributes of objects in the formal context. This article proposes a method to generate non-redundant implication base of a formal context with some constraints which restricting the formal context. In this case, non-redundant implicational base means that the implicational base does not contain all attribute implications which can be inferred from the others together with information of the constraints. This article also proposes a formulation to check the redundant attribute implications and encoding the problem into satisfiability (SAT) problem such that the problem can be solved by SAT Solver, a software which can solve a SAT problem. After implementation, an experiment shows that the proposed method is able to check the redundant attribute implication and generates a non-redundant implicational base of formal context with constraints.
| S-EPMC10909189 | biostudies-literature
Project description:The neural representation of concepts is a focus of many cognitive neuroscience studies. Prior works studying concept representation with neural imaging data have been largely limited to concrete concepts. The use of relatively small and constrained sets of stimuli leaves open the question of whether the findings can generalize other concepts. We share an fMRI dataset in which 11 participants thought of 672 individual concepts, including both concrete and abstract concepts. The concepts were probed using words paired with images in which the words were selected to cover a wide range of semantic categories. Furthermore, according to the componential theories of concept representation, we collected the 54 semantic features of the 672 concepts comprising sensory, motor, spatial, temporal, affective, social, and cognitive experiences by crowdsourcing annotations. The quality assessment results verify this as a high-quality neuroimaging dataset. Such a dataset is well suited to study how the brain represents different semantic features and concepts, creating the essential condition to investigate the neural representation of individual concepts.
| S-EPMC9691698 | biostudies-literature