An environment can be searched far more efficiently if the appropriate search strategy is used. Because of limited individual abilities swarm robots, namely, local sensing and low processing power, random searching main used in robotics. The walk methods that are most commonly Brownian motion Lévy flight, both which mimic self-organized behavior social insects. However, somewhat when applied to robotics, where having robots repeatedly result highly inefficient searching. Therefore, by...

Abstract Background Aptamer-protein interacting pairs play a variety of physiological functions and therapeutic potentials in organisms. Rapidly effectively predicting aptamer-protein is significant to design aptamers binding certain interested proteins, which will give insight into understanding mechanisms developing aptamer-based therapies. Results In this study, an ensemble method presented predict with hybrid features. The features for are extracted from Pseudo K-tuple Nucleotide...

Bacteriophage virion proteins and non-virion have distinct functions in biological processes, such as specificity determination for host bacteria, bacteriophage replication transcription. Accurate identification of from protein sequences is significant to understand the complex virulence mechanism bacteria influence bacteriophages on development antibacterial drugs. In this study, an ensemble method prediction put forward with hybrid feature spaces incorporating CTD (composition, transition...

The Golgi Apparatus (GA) is a major collection and dispatch station for numerous proteins destined secretion, plasma membranes lysosomes. dysfunction of GA can result in neurodegenerative diseases. Therefore, accurate identification protein subGolgi localizations may assist drug development understanding the mechanisms involved various cellular processes. In this paper, new computational method proposed identifying cis-Golgi from trans-Golgi proteins. Based on concept Common Spatial Patterns...

As critical components of DNA, enhancers can efficiently and specifically manipulate the spatial temporal regulation gene transcription. Malfunction or dysregulation is implicated in a slew human pathology. Therefore, identifying their strength may provide insights into molecular mechanisms transcription facilitate discovery candidate drug targets. In this paper, new enhancer its predictor, iEnhancer-GAN, proposed based on deep learning framework combination with word embedding sequence...

Antioxidant proteins perform significant functions in maintaining oxidation/antioxidation balance and have potential therapies for some diseases. Accurate identification of antioxidant could contribute to revealing physiological processes developing novel antioxidation-based drugs. In this study, an ensemble method is presented predict with hybrid features, incorporating SSI (Secondary Structure Information), PSSM (Position Specific Scoring Matrix), RSA (Relative Solvent Accessibility), CTD...

Current target detection methods have achieved high accuracy for detecting large and medium-sized targets. However, due to factors such as the small number of pixels features available targets in images, performance is generally unsatisfactory. In addition, real-time also critical. conclusion, a modified lightweight architecture detection, i.e., MBAB-YOLO, proposed based on You Only Look Once (YOLO) model by combining channel-wise attention block, space-attention block multi-branch-ConvNet...

The extracellular matrix (ECM) is a dynamic composite of secreted proteins that play important roles in numerous biological processes such as tissue morphogenesis, differentiation and homeostasis. Furthermore, various diseases are caused by the dysfunction ECM proteins. Therefore, identifying these may assist understanding related drug development. In view serious imbalance training dataset, Random Forest-based ensemble method with hybrid features developed this paper to identify Hybrid...

Cancerlectins have an inhibitory effect on the growth of cancer cells and are currently being employed as therapeutic agents. The accurate identification cancerlectins should provide insight into molecular mechanisms cancers. In this study, a new computational method based RF (Random Forest) algorithm is proposed for further improving performance identifying cancerlectins. Hybrid feature space before selection developed by combining different individual spaces, CTD (Composition, Transition,...

The DNA replication influences the inheritance of genetic information in life cycle. As distribution origins (ORIs) is major determinant to precisely regulate process, correct identification ORIs significant giving an insightful understanding mechanisms and regulatory expressions. For eukaryotes particular, multiple exist each their gene sequences complete a reasonable period time. To simplify process eukaryote's ORIs, most existing methods are developed by traditional machine learning...

Antifreeze proteins (AFPs) play a pivotal role in the antifreeze effect of overwintering organisms. They have wide range applications numerous fields, such as improving production crops and quality frozen foods. Accurate identification AFPs may provide important clues to decipher underlying mechanisms ice-binding facilitate selection most appropriate for several applications. Based on an ensemble learning technique, this study proposes AFP system called AFP-Ensemble. In system, random forest...

Oxidative stress can damage major cell components, including protein, DNA, lipid and membranes, which may make cells lose function induce a wide variety of diseases. As an extensive kind antioxidants in human animals, antioxidant proteins are essential to eliminate aging problems caused by oxidative stress. Accurate identification is significant step reveal the inducement physiological process certain types diseases aging. Furthermore, newly identified provide candidate targets for curing or...

Circular RNAs (circRNAs) are specifically and abnormally expressed in disease tissues, thus can be used as biomarkers to diagnose relevant diseases. Predicting circRNA-disease associations will provide essential clues reveal molecular mechanisms of development discover novel therapeutic targets. Existing algorithms ignore the heterogeneous biological association information related microRNAs (miRNAs). Based on a graph embedding model, prediction method called HGECDA is developed this paper....

As a complication of malignant tumors, brain metastasis (BM) seriously threatens patients’ survival and quality life. Accurate detection BM before determining radiation therapy plans is paramount task. Due to the small size heterogeneous number BMs, their manual diagnosis faces enormous challenges. Thus, MRI-based artificial intelligence-assisted significant. Most existing deep learning (DL) methods for automatic try ensure good trade-off between precision recall. However, due objective...