The prediction of interaction sites between circular RNA (circRNA) and binding proteins (RBPs) is crucial for regulating diseases discovering new treatment approaches. Computational models have been widely used to predict circRNA-RBP due the availability genome-wide circRNA event data. However, efficiently obtaining multi-scale features improve accuracy remains a challenging problem. In this study, we propose SSCRB, lightweight model predicting sites. Our extracts both sequence structural...

The Pandemic covid-19 spread globally has been given impact in the tourism industry, especially destination. This study investigated to build concept and theoretical framework that explains decision of local tourist intention visit a destination Indonesia post-pandemic covid-19. was considered perception Covid-19, non-pharmaceutical intervention health consciousness by implying Theory Planned Behavior constructs. study, is moderator variable predict Structural Equation Model-Partial Least...

Sustainability is one of the current much-discussed issues in world, including tourism sectors. However, there are few studies on management and marketing toward sustainable tourism. This study aims to analyze literature by using a bibliometric analysis approach based Web Science (WOS) database. A sample 528 articles was analyzed this study. The data were processed results graphically presented R program. found occurrence publications year, publication source information authors, journals,...

Deep learning-based molecular generative models have garnered emerging attention for their capability to generate molecules with novel structures and desired physicochemical properties. However, the evaluation of these models, particularly in a biological context, remains insufficient. To address limitations existing metrics emulate practical application scenarios, we construct RediscMol benchmark that comprises active extracted from 5 kinase 3 GPCR data sets. A set rediscovery-...

Research in recommender systems is now starting to recognise the importance of multiple selection criteria improve recommendation output. In this paper, we present a novel approach multi-criteria recommendation, based on idea clustering users "preference lattices" (partial orders) according their preferences. We assume that some for an item (product or service) will dominate overall ranking, and these dominant be different users. Following assumption, cluster preferences, creating lattice"....

Abstract Binding affinity prediction largely determines the discovery efficiency of lead compounds in drug discovery. Recently, machine learning (ML)-based approaches have attracted much attention hopes enhancing predictive performance traditional physics-based approaches. In this study, we evaluated impact structural dynamic information on binding by comparing models trained different dimensional descriptors, using three targets (i.e. JAK1, TAF1-BD2 and DDR1) their corresponding ligands as...

Abstract With the fast‐growing and evolving omics data, demand for streamlined adaptable tools to handle bioinformatics analysis continues grow. In response this need, Automated Bioinformatics Analysis (AutoBA) is introduced, an autonomous AI agent designed explicitly fully automated multi‐omic analyses based on large language models (LLMs). AutoBA simplifies analytical process by requiring minimal user input while delivering detailed step‐by‐step plans various tasks. AutoBA's unique...

Traditional screening methods for Mild Cognitive Impairment (MCI) face limitations in accessibility and scalability. To address this, we developed validated a speech-based automatic app implementing three speech–language tasks with user-centered design server–client architecture. The integrates automated speech processing SVM classifiers MCI detection. Functionality validation included comparison manual assessment testing real-world settings (n = 12), user engagement evaluated separately...

Amplified by CRISPR-Cas12a and DNA nanomachines, the sensitive detection of HPV-16 in human serum was performed using mass spectrometry.

The introduction of AlphaFold2 (AF2) has sparked significant enthusiasm and generated extensive discussion within the scientific community, particularly among drug discovery researchers. Although previous studies have addressed performance AF2 structures in virtual screening (VS), a more comprehensive investigation is still necessary considering paramount importance structural accuracy design. In this study, we evaluate VS across three common scenarios: targets with holo, apo, structures;...

This study aims to review the documents in disasters, risk and crises produce a generic model for developing holistic framework tourism hospitality industry. uses bibliometric analysis systematic narrative of 795 from Web Science Scopus databases determine number publications, top authors, cited documents, journals, regional distribution, mapping topic trends, structure crises, type crises. The results find some issues disaster such as management, resilience, recovery risk, presents...

A fixed point of the strictly pseudocontractive mapping is obtained as limit an iteratively constructed sequence with error estimation in general Banach spaces.

The contribution of this paper is a conceptual architecture based on intelligent services for manufacturing support systems. Current approaches cannot cope with the dynamism inherent in domain, where unexpected and drastic changes occur at any time affect cross-boundary Our approach alleviates these issues focuses need supporting real-time automatic negotiation, planning, scheduling optimisation, intra across factories. We present an execution example our aerospace industry, instantiating...

In this paper, we propose a new simultaneous iterative algorithm for solving the split common fixed point problem of directed operators. Inspired by idea cyclic algorithm, also introduce two algorithms which combine process and together. Under mild assumptions, prove convergence proposed sequences. As applications, obtain several iteration schemes to solve inverse multiple-sets feasibility problem. Numerical experiments are presented confirm efficiency algorithms.

The COVID-19 outbreak has altered how visitors live, including in the tourism sector. current study investigates tourist behavior virtual during pandemic using framework of theory planned (TPB) and intention. included 217 people who utilized for tourists' pandemic. data are analyzed Structural Equation Modelling Partial Least Squares (SEM-PLS). According to findings, TPB framework, such as attitude toward tourism, subjective norms, perceived control, have a favorable substantial influence on...

The prediction of drug-target affinity (DTA) plays a crucial role in drug development and the identification potential targets. In recent years, computer-assisted DTA has emerged as significant approach this field. study, we propose multi-modal deep learning framework called MMD-DTA for predicting binding regions. model can predict while simultaneously regions interactions through unsupervised learning. To achieve this, first uses graph neural networks target structural feature extraction...

The split common fixed point problem has been investigated recently, which is a generalization of the feasibility and convex problem. We construct cyclic algorithm to approximate solution for demicontractive mappings in Hilbert space. Our results improve extend previously discussed related problems algorithms.

The prediction of drug–target interaction (DTI) is crucial to drug discovery. Although the interactions between and target can be accurately verified by traditional biochemical experiments, determination DTI through experiments a time-consuming, laborious, expensive process. Therefore, we propose learning-based framework named BG-DTI for prediction. Our model combines two main approaches based on biological features heterogeneous networks identify drugs targets. First, extract original from...