A5100650157- EEG and Brain-Computer Interfaces
- Protein Structure and Dynamics
- Genetics, Aging, and Longevity in Model Organisms
- Neural dynamics and brain function
- Enzyme Structure and Function
- Blind Source Separation Techniques
- Functional Brain Connectivity Studies
- Spaceflight effects on biology
- Neuroscience and Neural Engineering
- Genomics and Phylogenetic Studies
- Machine Learning in Bioinformatics
- Emotion and Mood Recognition
- Advanced Memory and Neural Computing
- Photoreceptor and optogenetics research
- Microbial Metabolic Engineering and Bioproduction
- Image and Signal Denoising Methods
- ECG Monitoring and Analysis
- Image and Video Quality Assessment
- Advanced MRI Techniques and Applications
- Gaze Tracking and Assistive Technology
- Biofield Effects and Biophysics
- Plant Reproductive Biology
- Multisensory perception and integration
- Iterative Learning Control Systems
- Advanced Image Fusion Techniques
Beihang University
2023-2024
Xinyu University
2024
Hunan University of Traditional Chinese Medicine
2024
Health and Family Planning Commission of Hunan Province
2024
University of South China
2024
Chongqing University of Posts and Telecommunications
2013-2023
Affiliated Hospital of Hangzhou Normal University
2023
South China Normal University
2023
South Central Minzu University
2019-2022
China Medical University
2018-2021
Deep learning technology is rapidly spreading in recent years and has been extensive attempts the field of Brain-Computer Interface (BCI).Though accuracy Motor Imagery (MI) BCI systems based on deep have greatly improved compared with some traditional algorithms, it still a big problem to clearly interpret models.To address issues, this work first introduces popular model EEGNet compares algorithm Filter-Bank Common Spatial Pattern (FBCSP).After that, considers that 1-D convolution can be...
Abstract Background Disordered regions are segments of the protein chain which do not adopt stable structures. Such often interest because they have a close relationship with expression and functionality. As such, disorder prediction is important for structure prediction, determination function annotation. Results This paper presents our server, PreDisorder. It based on ab initio method (MULTICOM-CMFR) which, along meta (or consensus) (MULTICOM), was recently ranked among top predictors in...
The protein structure prediction problem continues to elude scientists. Despite the introduction of many methods, only modest gains were made over last decade for certain classes targets. To address this challenge, a social-media based worldwide collaborative effort, named WeFold, was undertaken by 13 labs. During collaboration, laboratories simultaneously competing with each other. Here, we present first attempt at "coopetition" in scientific research applied and refinement problems....
Abstract Background Accurate identification of protein domain boundaries is useful for structure determination and prediction. However, predicting from a sequence still very challenging largely unsolved. Results We developed new method to integrate the classification power machine learning with evolutionary signals embedded in families order improve boundary The first extracts putative multiple alignment between query its homologs. sites are then classified scored by support vector machines...
As genome sequencing is becoming routine in biomedical research, the total number of protein sequences increasing exponentially, recently reaching over 108 million. However, only a tiny portion these proteins (i.e. ~75,000 or < 0.07%) have solved tertiary structures determined by experimental techniques. The gap between sequence and structure continues to enlarge rapidly as throughput techniques much higher than that determination Computational software tools for predicting structural...
Depression affects many people around the world today and is considered a global problem. Electroencephalogram (EEG) measurement an appropriate way to understand underlying mechanisms of major depressive disorder (MDD) distinguish depression from normal control. With development deep learning methods, researchers have adopted models improve classification accuracy recognition. However, there are few studies on designing convolution filters for spatial frequency domain feature in different...
Motor imagery Electroencephalogram (EEG) signals have been widely used in the field of brain-computer interface (BCI) due to their advantage non-invasiveness and easy acquisition. However, distortions temporal local information EEG signal inter-subject variability, it is very time-consuming perform a calibration procedure designed subject-specific manner, which requires large number labeled samples. To this end, we construct brain graph based on electrode distribution propose new subdomain...
Multiple Sequence Alignment (MSA) is a basic tool for bioinformatics research and analysis. It has been used essentially in almost all tasks such as protein structure modeling, gene function prediction, DNA motif recognition, phylogenetic Therefore, improving the accuracy of multiple sequence alignment important advancing many fields. We designed developed new method, MSACompro, to synergistically incorporate predicted secondary structure, relative solvent accessibility, residue-residue...
Abstract Background Predicting protein structure from sequence is one of the most significant and challenging problems in bioinformatics. Numerous bioinformatics techniques tools have been developed to tackle almost every aspect prediction ranging structural feature prediction, template identification query-template alignment sampling, model quality assessment, refinement. How synergistically select, integrate improve strengths complementary at each stage build a high-performance system...
Machine learning is increasingly popular and promising in environmental science due to its potential solving various problems, particularly with simple code-free tools.
Protein disordered regions are segments of a protein chain that do not adopt stable structure. Thus far, variety disorder prediction methods have been developed and widely used, only in traditional bioinformatics domains, including structure prediction, determination function annotation, but also many other biomedical fields. The relationship between intrinsically-disordered proteins some human diseases has played significant role disease identification epidemiological investigations....