Abstract Motivation The rapid development of single-cell RNA sequencing (scRNA-seq) has significantly advanced biomedical research. Clustering analysis, crucial for scRNA-seq data, faces challenges including data sparsity, high dimensionality, and variable gene expressions. Better low-dimensional embeddings these complex should maintain intrinsic information while making similar close dissimilar distant. However, existing methods utilizing neural networks typically focus on minimizing...

Co-clustering methods make use of the correlation between samples and attributes to explore co-occurrence structure in data. These have played a significant role gene expression analysis, image segmentation, document clustering. In bipartite graph partition-based co-clustering methods, relationship is described by constructing diagonal symmetric matrix, which clustered philosophy spectral However, this not only has high time complexity but also same number row column clusters. fact,...

AbstractIn this article we show that the Voronoi-based nine-intersection (V9I) model proposed by Chen et al. (2001, A 9-intersection for spatial relations. International Journal of Geographical Information Science, 15 (3), 201–220) is more expressive than what has been believed before. Given any two entities and B, V9I relation between B represented as a 3 × Boolean matrix. For each pair types is, points, lines, regions, first most matrices do not represent using topological constraints...

We introduce, study, and evaluate a novel algorithm in the context of qualitative constraint-based spatial temporal reasoning, that is based on idea variable elimination, simple general exact inference approach probabilistic graphical models. Given constraint network N, our enforces particular directional local consistency which we denote by ←-consistency. Our discussion restricted to distributive subclasses relations, i.e., sets relations closed under converse, intersection, weak...

Qualitative calculi play a central role in representing and reasoning about qualitative spatial temporal knowledge. This paper studies distributive subalgebras of calculi, which are (weak) composition distributives over nonempty intersections. It has been proven for RCC5 RCC8 that path consistent constraint network subalgebra is always minimal globally (in the sense strong $n$-consistency) sense. The well-known subclass convex interval relations provides one such an example subalgebras....

This paper develops a new mechanism to efficiently compute and compactly store qualitative spatial relations between objects, focusing on topological directional for large datasets of region objects. The central idea is use minimum bounding rectangles (MBRs) approximately represent objects with arbitrary shape complexity only that cannot be unambiguously inferred from the corresponding MBRs. We demonstrate, both in theory practice, our approach requires considerably less construction time...

Representing belief information is a fundamental problem in the field of revision. The AGM framework uses deductively closed set formulas, known as theory, to represent an agent, because rational agent should satisfy properties similar theory. However, iterated revision setting, DP conditional beliefs like (φ | ψ) such information, which not natural, are formulas and logical connections between them cannot be characterized clearly. In this paper, we propose novel logic system for...

We introduce and study a notion of robustness in Qualitative Constraint Networks (QCNs), which are typically used to represent reason about abstract spatial temporal information. In particular, given QCN, we interested obtaining robust qualitative solution, or, scenario it, is satisfiable that has higher perturbation tolerance than any other, other words, more chances remain valid after it altered. This challenging problem requires consider the entire set scenarios whose size usually...

We introduce, study, and evaluate a novel algorithm in the context of qualitative constraint-based spatial temporal reasoning that is based on idea variable elimination, simple general exact inference approach probabilistic graphical models. Given constraint network [Formula: see text], our utilizes particular directional local consistency, which we denote by text]-consistency, order to efficiently decide satisfiability text]. Our discussion restricted distributive subclasses relations,...

Multiple myeloma (MM) is a prevalent hematological malignancy that poses significant challenges for treatment. Dysregulated cholesterol metabolism has been linked to tumorigenesis, disease progression, and therapy resistance. However, the correlation between metabolism-related genes (CMGs) prognosis of MM remains unclear. Univariate Cox regression analysis LASSO were applied construct an overall survival-related signature based on Gene Expression Omnibus database. The was validated using...

Dimensionality reduction is a fundamental and important research topic in the field of machine learning. This paper focuses on dimensionality technique that exploits semi-supervising information form pairwise constraints; specifically, these constraints specify whether two instances belong to same class or not. We propose dual linear methods accomplish under setting. These overcome difficulty maximizing between-class difference minimizing within-class at time, by transforming original data...