Interdisciplinary Sciences, Computational Life Sciences 
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This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.scFED: Clustering Identifying Cell Types of scRNA-Seq Data Based on Feature Engineering Denoising
In this study, we introduce scFED, a feature-engineered gene selection framework. scFED identifies prospective feature sets to eliminate the noise fluctuation. And fuse them with existing knowledge from the tissue-specific cellular taxonomy reference database (CellMatch) to avoid the influence of subjective factors. Then present a reconstruction approach for noise reduction and crucial information amplification. We apply scFED on four genuine single-cell datasets and compare it with other techniques. According to the results, scFED improves clustering, decreases dimension of the scRNA-seq data, improves cell type identific...
Source: Interdisciplinary Sciences, Computational Life Sciences - July 4, 2023 Category: Bioinformatics Source Type: research
Exploring the Binding Mechanism of NRG1 –ERBB3 Complex and Discovery of Potent Natural Products to Reduce Diabetes-Assisted Breast Cancer Progression
In conclusion, this complex may represent a residue-specific drug target to inhibit BC progression.Graphical abstract (Source: Interdisciplinary Sciences, Computational Life Sciences)
Source: Interdisciplinary Sciences, Computational Life Sciences - June 30, 2023 Category: Bioinformatics Source Type: research
CD47Binder: Identify CD47 Binding Peptides by Combining Next-Generation Phage Display Data and Multiple Peptide Descriptors
AbstractCD47/SIRP α pathway is a new breakthrough in the field of tumor immunity after PD-1/PD-L1. While current monoclonal antibody therapies targeting CD47/SIRPα have demonstrated some anti-tumor effectiveness, there are several inherent limitations associated with these formulations. In the paper, we developed a predictive model that combines next-generation phage display (NGPD) and traditional machine learning methods to distinguish CD47 binding peptides. First, we utilized NGPD biopanning technology to screen CD47 binding peptides. Second, ten traditional machine learning methods based on multiple peptid e descripto...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 30, 2023 Category: Bioinformatics Source Type: research
G4Bank: A database of experimentally identified DNA G-quadruplex sequences
AbstractG-quadruplex (G4), a non-canonical nucleic acid structure, has been suggested to play a key role in important cellular processes including transcription, replication and cancer development. Recently, high-throughput sequencing approaches for G4 detection have provided a large amount of experimentally identified G4 data that reveal genome-wide G4 landscapes and enable the development of new methods for predicting potential G4s from sequences. Although several existing databases provide G4 experimental data and relevant biological information from different perspectives, there is no dedicated database to collect and ...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 30, 2023 Category: Bioinformatics Source Type: research
LDAEXC: LncRNA –Disease Associations Prediction with Deep Autoencoder and XGBoost Classifier
AbstractNumerous scientific evidences have revealed that long non-coding RNAs (lncRNAs) are involved in the progression of human complex diseases and biological life activities. Therefore, identifying novel and potential disease-related lncRNAs is helpful to diagnosis, prognosis and therapy of many human complex diseases. Since traditional laboratory experiments are cost and time-consuming, a great quantity of computer algorithms have been proposed for predicting the relationships between lncRNAs and diseases. However, there are still much room for the improvement. In this paper, we introduce an accurate framework named LD...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 12, 2023 Category: Bioinformatics Source Type: research
Integration of IDPC Clustering Analysis and Interpretable Machine Learning for Survival Risk Prediction of Patients with ESCC
AbstractPrecise forecasting of survival risk plays a pivotal role in comprehending and predicting the prognosis of patients afflicted with esophageal squamous cell carcinoma (ESCC). The existing methods have the problems of insufficient fitting ability and poor interpretability. To address this issue, this work proposes a novel interpretable survival risk prediction method for ESCC patients based on extreme gradient boosting improved by whale optimization algorithm (WOA-XGBoost) and shapley additive explanations (SHAP). Given the imbalanced nature of the data set, the adaptive synthetic sampling (ADASYN) is first used to g...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 30, 2023 Category: Bioinformatics Source Type: research
A Self-attention Graph Convolutional Network for Precision Multi-tumor Early Diagnostics with DNA Methylation Data
AbstractDNA methylation-based precision tumor early diagnostics is emerging as state-of-the-art technology that could capture early cancer signs 3 ~ 5 years in advance, even for clinically homogenous groups. Presently, the sensitivity of early detection for many tumors is ~ 30%, which needs significant improvement. Nevertheless, based on the genome-wide DNA methylation data, one could comprehensively characterize tumors’ entire mol ecular genetic landscape and their subtle differences. Therefore, novel high-performance methods must be modeled by considering unbiased information using excessively available DNA m...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 29, 2023 Category: Bioinformatics Source Type: research
CRBP-HFEF: Prediction of RBP-Binding Sites on circRNAs Based on Hierarchical Feature Expansion and Fusion
AbstractCircular RNAs (circRNAs) participate in the regulation of biological processes by binding to specific proteins and thus influence transcriptional processes. In recent years, circRNAs have become an emerging hotspot in RNA research. Due to powerful learning ability, the various deep learning frameworks have been used to predict the binding sites of RNA-binding protein (RPB) on circRNAs. These methods usually perform only single-level feature extraction of sequence information. However, the feature acquisition may be inadequate for single-level extraction. Generally, the features of deep and shallow layers of neural ...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 26, 2023 Category: Bioinformatics Source Type: research
BMRI-NET: A Deep Stacked Ensemble Model for Multi-class Brain Tumor Classification from MRI Images
AbstractBrain tumors are one of the most dangerous health problems for adults and children in many countries. Any failure in the diagnosis of brain tumors may lead to shortening of human life. Accurate and timely diagnosis of brain tumors provides appropriate treatment to increase the patient's chances of survival. Due to the different characteristics of tumors, one of the challenging problems is the classification of three types of brain tumors. With the advent of deep learning (DL) models, three classes of brain tumor classification have been addressed. However, the accuracy of these methods requires significant improvem...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 12, 2023 Category: Bioinformatics Source Type: research
An Improved Soft Subspace Clustering Algorithm Based on Particle Swarm Optimization for MR Image Segmentation
In conclusion, the extended noise clustering method is implemented in order to maximize the weight. Additionally, the constraint condition of the weight is changed from the equality constraint to the boundary constraint in order to reduce the impact of noise. The methodology presented in this research works to reduce the amount of sensitivity the SSC algorithm has to noisy data. It is possible to demonstrate the efficacy of this algorithm by using photos with noise already present or by introducing noise to existing photographs. The revised SSC approach based on particle swarm optimization (PSO) is demonstrated to have sup...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 10, 2023 Category: Bioinformatics Source Type: research
Spatial –Temporal EEG Fusion Based on Neural Network for Major Depressive Disorder Detection
AbstractIn view of the major depressive disorder characteristics such as high mortality as well as high recurrence, it is important to explore an objective and effective detection method for major depressive disorder. Considering the advantages complementary of different machine learning algorithms in information mining process, as well as the fusion complementary of different information, in this study, the spatial –temporal electroencephalography fusion framework using neural network is proposed for major depressive disorder detection. Since electroencephalography is a typical time series signal, we introduce recurrent...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 4, 2023 Category: Bioinformatics Source Type: research
RNA Folding Based on 5 Beads Model and Multiscale Simulation
AbstractRNA folding prediction is very meaningful and challenging. The molecular dynamics simulation (MDS) of all atoms (AA) is limited to the folding of small RNA molecules. At present, most of the practical models are coarse grained (CG) model, and the coarse-grained force field (CGFF) parameters usually depend on known RNA structures. However, the limitation of the CGFF is obvious that it is difficult to study the modified RNA. Based on the 3 beads model (AIMS_RNA_B3), we proposed the AIMS_RNA_B5 model with three beads representing a base and two beads representing the main chain (sugar group and phosphate group). We fi...
Source: Interdisciplinary Sciences, Computational Life Sciences - April 28, 2023 Category: Bioinformatics Source Type: research
Identifying Lymph Node Metastasis-Related Factors in Breast Cancer Using Differential Modular and Mutational Structural Analysis
AbstractComplex diseases are generally caused by disorders of biological networks and/or mutations in multiple genes. Comparisons of network topologies between different disease states can highlight key factors in their dynamic processes. Here, we propose a differential modular analysis approach that integrates protein –protein interactions with gene expression profiles for modular analysis, and introduces inter-modular edges and date hubs to identify the “core network module” that quantifies the significant phenotypic variation. Then, based on this core network module, key factors, including functional prot ein–pr...
Source: Interdisciplinary Sciences, Computational Life Sciences - April 28, 2023 Category: Bioinformatics Source Type: research
A Novel Image Encryption Scheme for DNA Storage Systems Based on DNA Hybridization and Gene Mutation
AbstractWith the rapid development of DNA (deoxyribonucleic acid) storage technologies, storing digital images in DNA is feasible. Meanwhile, the information security in DNA storage system is still a problem to solve. Therefore, in this paper, we propose a DNA storage-oriented image encryption algorithm utilizing the information processing mechanisms in molecule biology. The basic idea is to perform pixel replacement by gene hybridization, and implement dual diffusion by pixel diffusion and gene mutation. The ciphertext DNA image can be synthesized and stored in DNA storage system after encryption. Experimental results dem...
Source: Interdisciplinary Sciences, Computational Life Sciences - April 4, 2023 Category: Bioinformatics Source Type: research
dbMisLoc: A Manually Curated Database of Conditional Protein Mis-localization Events
AbstractOver the last few years, an increasing number of protein mis-localization events have been reported under various conditions. It is important to understand these events and their relationship with complex disorders. Although many efforts had been made in establishing models with statistical or machine learning algorithms, a comprehensive database resource is still missing. Since the records of experimental-validated protein mis-localization events spread across many literatures, a collection of all these reports in a unique website is demanded. In this paper, we created the dbMisLoc database by manually curating co...
Source: Interdisciplinary Sciences, Computational Life Sciences - March 31, 2023 Category: Bioinformatics Source Type: research
