Population characteristic exploitation-based multi-orientation multi-objective gene selection for microarray data classification.

Gene selection is a process of selecting discriminative genes from microarray data that helps to diagnose and classify cancer samples effectively. Swarm intelligence evolution-based gene selection algorithms can never circumvent the problem that the population is prone to local optima in the process of gene selection. To tackle this challenge, previous research has focused primarily on two aspects: mitigating premature convergence to local optima and escaping from local optima. In contrast to these strategies, this paper introduces a novel perspective by adopting reverse thinking, where the issue of local optima is seen as an opportunity rather than an obstacle. Building on this foundation, we propose MOMOGS-PCE, a novel gene selection approach that effectively exploits the advantageous characteristics of populations trapped in local optima to uncover global optimal solutions. Specifically, MOMOGS-PCE employs a novel population initialization strategy, which involves the initialization of multiple populations that explore diverse orientations to foster distinct population characteristics. The subsequent step involved the utilization of an enhanced NSGA-II algorithm to amplify the advantageous characteristics exhibited by the population. Finally, a novel exchange strategy is proposed to facilitate the transfer of characteristics between populations that have reached near maturity in evolution, thereby promoting further population evolution and enhancing the search for more optimal gene subsets. The experimental results demonstrated that MOMOGS-PCE exhibited significant advantages in comprehensive indicators compared with six competitive multi-objective gene selection algorithms. It is confirmed that the "reverse-thinking" approach not only avoids local optima but also leverages it to uncover superior gene subsets for cancer diagnosis.

Drug innovation and reverse thinking / 药学学报

Drug innovation involves an individual molecular operation, and every new molecular entity features a hard-duplicated track of R&D. The transformation from an active compound to a new medicine carries out almost in a chaotic system devoid of regularity and periodic alteration. Since new millennium the dominant position in drug innovation has been occupied by the first-in-class drugs, yet the number of launched follow-on drugs has been distinctly decreased. The innovation of first-in-class drugs is characterized by a high risk throughout the whole process. To achieve initiative and uniqueness of drug discovery, the strategy and method of the inverse thinking might be a feasible way, because the inertial and conformity thinkings in drug discovery normally lead to ensemble with similar drug category. However, the study from the flipside or opposite of things (e.g. targets or effects) brand new routes might be opened. This article is to describe the strategy of reverse thinking in drug discovery by some examples including opioid receptor antagonist eluxadoline, HSP90 activator, hERG channel agonist, covalent drugs, and ultra-small drugs.

Exploration and analysis on the teaching of pharmacology in clinical medicine speciality-the reverse thinking teaching / 中华医学教育探索杂志

on the basis of analyzing the teaching methods available.the article explores the reverse thinking teaching method of Pharmacdogy and the characteristics of the course and the students,in order to stimulate students'interest and initiative in study as well as culture their clinical thinking ability.