Oscar Ramírez | Searcharxiv

arXiv2025

Propositional Calculus with Multiple Negations

One advantage of paraconsistent logic is that it can deal with inconsistencies without making the system trivial. However, unlike classical propositional calculus, its deductive system is limited, and the meaning of paraconsistent negation is still not clear. This article presents a logical system that brings together the strengths of both approaches. The Propositional Calculus with Multiple Negations $\left(\textbf{CPN}_{n}\right)$ is a generalization of classical propositional logic in which a finite number of negations (each weaker than the classical one but with similar behavior) are added. This makes it possible to introduce weak inconsistencies in a controlled way without leading to triviality.

math.LO↗

arXiv2022

Feature extraction using Spectral Clustering for Gene Function Prediction using Hierarchical Multi-label Classification

Gene annotation addresses the problem of predicting unknown associations between gene and functions (e.g., biological processes) of a specific organism. Despite recent advances, the cost and time demanded by annotation procedures that rely largely on in vivo biological experiments remain prohibitively high. This paper presents a novel in silico approach for to the annotation problem that combines cluster analysis and hierarchical multi-label classification (HMC). The approach uses spectral clustering to extract new features from the gene co-expression network (GCN) and enrich the prediction task. HMC is used to build multiple estimators that consider the hierarchical structure of gene functions. The proposed approach is applied to a case study on Zea mays, one of the most dominant and productive crops in the world. The results illustrate how in silico approaches are key to reduce the time and costs of gene annotation. More specifically, they highlight the importance of: (i) building new features that represent the structure of gene relationships in GCNs to annotate genes; and (ii) taking into account the structure of biological processes to obtain consistent predictions.

cs.LG↗