A5100386395- Neural Networks and Applications
- Viral Infectious Diseases and Gene Expression in Insects
- Gene Regulatory Network Analysis
- Machine Learning in Bioinformatics
- Stock Market Forecasting Methods
- Evolutionary Algorithms and Applications
- Renal cell carcinoma treatment
- Solar Thermal and Photovoltaic Systems
- Cancer, Hypoxia, and Metabolism
- Peptidase Inhibition and Analysis
- Neural Networks and Reservoir Computing
- Advanced Decision-Making Techniques
- RNA and protein synthesis mechanisms
- Genetics, Bioinformatics, and Biomedical Research
- Computational Drug Discovery Methods
- Prion Diseases and Protein Misfolding
- Gene expression and cancer classification
- Family Support in Illness
- Educational Technology and Assessment
- Cancer, Lipids, and Metabolism
- Solar Radiation and Photovoltaics
- Bioinformatics and Genomic Networks
- Advanced Algorithms and Applications
- Cancer survivorship and care
- Traditional Chinese Medicine Studies
First Hospital of Jilin University
2025
Jilin University
2025
Linyi People's Hospital
2024
Linyi University
2024
Shanghai East Hospital
2022
Zaozhuang University
2016-2021
Ningbo Medical Center Lihuili Hospital
2020
Nankai University
2019
State Key Laboratory of Medicinal Chemical Biology
2019
Qilu Hospital of Shandong University
2008
Abstract Protein is an essential component of the living organism. The prediction protein-protein interactions (PPIs) has important implications for understanding behavioral processes life, preventing diseases, and developing new drugs. Although development high-throughput technology makes it possible to identify PPIs in large-scale biological experiments, restricts extensive use experimental methods due constraints time, cost, false positive rate other conditions. Therefore, there urgent...
An unnatural monosaccharide with a C6-azide, Ac36AzGalNAc, has been developed as potent and selective probe for O-GlcNAc-modified proteins. Combined click chemistry, we demonstrate that Ac36AzGalNAc can robustly label O-GlcNAc glycosylation in wide range of cell lines. Meanwhile, imaging LC-MS/MS proteomics verify its activity on O-GlcNAc. More importantly, the protocol presented here provides general methodology tracking, capturing identifying modified proteins cells or lysates.
Abstract Background The growing researches of molecular biology reveal that complex life phenomena have the ability to demonstrating various types interactions in level genomics. To establish between genes or proteins and understand intrinsic mechanisms biological systems become an urgent need study hotspot. Results In order forecast gene expression data identify more accurate regulatory network, complex-valued version ordinary differential equation (CVODE) is proposed this paper. optimize...
Stock index prediction is considered as a difficult task in the past decade. In order to predict stock accurately, this paper proposes novel method based on S-system model. Restricted gene expression programming (RGEP) proposed encode and optimize structure of S-system. A hybrid intelligent algorithm brain storm optimization (BSO) particle swarm (PSO) parameters Five real market prices such Dow Jones Index, Hang Seng NASDAQ Shanghai Exchange Composite SZSE Component Index are collected...
Due to the complicated content system, and abstract, boring trivial knowledge points, C language programming is understood badly by fresh students. So an online offline teaching mode for proposed. In our mode, recorded videos about points are uploaded on Chaoxing website made as Massive Online Open Course (MOOC). Grammar exercises set website. Programming put Judge (OJ) platform. The students from Zaozhuang University could learn manners. Through implementation of one semester, investigation...
Abstract In recent years, many meta‐heuristic algorithms have been investigated to estimate the parameters of photovoltaic (PV) models. However, accuracy estimated still needs be concerned, especially for some complex PV models with unknown parameters. order more precisely and reliably, an efficient hybrid algorithm based on particle swarm optimisation teaching‐learning‐based (PSOTLBO) is proposed in this paper. PSOTLBO, inspired by learner phase (TLBO), improved designed introduced into...
In this paper, a novel Legendre neural network model is proposed, namely additive (ALNN). A new hybrid evolutionary method besed on binary particle swarm optimization (BPSO) algorithm and firefly proposed to optimize the structure parameters of ALNN model. Shanghai stock exchange composite index used evaluate performance ALNN. Results reveal that performs better than LNN
Introduction Urologic malignancies are the major causes of morbidity and mortality in men over 40 years old, accounting for more than 20% all malignant tumors. Several meta-analyses shown that statin exposure can reduce various urologic cancers. The adjuvant roles tumor prevention anti-tumor activity now being gradually recognized have gained attention. Nevertheless, to date, multiple clinical studies found inconsistent results their anti-cancer effects. This study aims evaluate credibility...
The detection and characterization of somatic mutations have become the important means to analyze occurrence development cancer and, ultimately, will help select effective precise treatment for specific patients. It is very difficult detect accurately from massive sequencing data. In this paper, a forest-graph-embedded deep feed-forward network (forgeNet) utilized forgeNet, random forest (RF) or Gradient Boosting Machine (GBM) graph-embedded (GEDFN) are extract features implement...
Abstract Background: The identification and prediction of Drug-Target Interaction (DTI) is the basis for screening drug candidates, which plays a vital role in development innovative drugs. However, due to time-consuming high cost constraints biological experimental methods, traditional target technologies are often difficult develop on large scale. Therefore, silico methods urgently needed predict drug-target interactions genome-wide manner. Results: In this article, we design new approach,...
Emerging evidence demonstrates that post-translational modification plays an important role in several human complex diseases. Nevertheless, considering the inherent high cost and time consumption of classical typical vitro experiments, increasing attention has been paid to development efficient available computational tools identify potential sites level protein. In this work, we propose a machine learning-based model called CirBiTree for identification citrullination sites. More...