A5038446460- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Gene Regulatory Network Analysis
- Computational Drug Discovery Methods
- CRISPR and Genetic Engineering
- Cancer Genomics and Diagnostics
- Ferroptosis and cancer prognosis
- Plant Virus Research Studies
- Cancer-related molecular mechanisms research
- Research in Cotton Cultivation
- Advanced Multi-Objective Optimization Algorithms
- Antibiotic Resistance in Bacteria
- Single-cell and spatial transcriptomics
- Metaheuristic Optimization Algorithms Research
- Genomics and Phylogenetic Studies
- Plant-Microbe Interactions and Immunity
- Machine Learning in Bioinformatics
- Radiomics and Machine Learning in Medical Imaging
- Plant Gene Expression Analysis
- Viral Infectious Diseases and Gene Expression in Insects
- Immune cells in cancer
- Circular RNAs in diseases
- Insect and Pesticide Research
- Evolutionary Algorithms and Applications
- Complex Network Analysis Techniques
Zhengzhou University
2019-2025
Beijing University of Technology
2025
China Medical University
2025
First Hospital of China Medical University
2025
Sun Yat-sen University
2022-2024
Sun Yat-sen University Cancer Center
2022-2024
Xinjiang Production and Construction Corps
2020-2024
Tarim University
2013-2024
Shandong University
2022-2024
Shanghai Institute of Hematology
2024
Constrained multiobjective optimization problems (CMOPs) involve multiple objectives to be optimized and various constraints satisfied, which challenges the evolutionary algorithms in balancing constraints. This article attempts explore utilize relationship between constrained Pareto front (CPF) unconstrained (UPF) solve CMOPs. Especially, for a given CMOP, process is divided into learning stage evolving stage. The purpose of measure CPF UPF. To this end, we first create two populations...
The inference of gene regulatory networks (GRNs) from expression data can mine the direct regulations among genes and gain deep insights into biological processes at a network level. During past decades, numerous computational approaches have been introduced for inferring GRNs. However, many them still suffer various problems, e.g., Bayesian (BN) methods cannot handle large-scale due to their high complexity, while information theory-based identify directions interactions also false...
Abstract Motivation It is a challenging task to discover personalized driver genes that provide crucial information on disease risk and drug sensitivity for individual patients. However, few methods have been proposed identify the personalized-sample from cancer omics data due lack of samples each individual. To circumvent this problem, here we present novel single-sample controller strategy (SCS) mutation profiles network controllability perspective. Results SCS integrates expression into...
Myeloid-derived suppressor cells (MDSCs) are major negative regulators of immune responses in cancer and chronic infections. It remains unclear if regulation MDSC activity different conditions is controlled by similar mechanisms. We compared MDSCs mice with lymphocytic choriomeningitis virus (LCMV) infection. Chronic LCMV infection caused the development monocytic (M-MDSCs) but did not induce polymorphonuclear (PMN-MDSCs). In contrast, both populations were present models. An acquisition...
Abstract Insects pose significant challenges in cotton‐producing regions. Here, they describe a high‐throughput CRISPR/Cas9‐mediated large‐scale mutagenesis library targeting endogenous insect‐resistance‐related genes cotton. This targeted 502 previously identified using 968 sgRNAs, generated ≈2000 T0 plants and achieved 97.29% genome editing with efficient heredity, reaching upto 84.78%. Several potential resistance‐related mutants (10% of 200 lines) their that may contribute to...
Although existing computational models have identified many common driver genes, it remains challenging to identify the personalized genes by using samples of an individual patient. Recently, methods exploiting structure-based control principles complex networks provide new clues for identifying minimum number nodes drive state transition large-scale from initial desired state. However, network cannot be directly applied due unknown dynamics system. Here we proposed model (PNC) employing...
Cotton (Gossypium hirsutum) is an allotetraploid species and a typical thermophilic crop that can survive grow well under temperatures up to 45 °C. CRISPR/LbCpf1 (LbCas12a) temperature-sensitive system for plant genome editing (Malzahn et al., 2019) has been successfully applied in such as rice, soya bean, tobacco, maize cotton (Lee 2019; Li 2018; Tang 2017; Xu 2019). However, the temperature sensitivity of LbCpf1 not tested yet, high temperature-resistant crop. In order improve efficiency...
Identifying the biomarkers from personalized gene interaction network of individual patients is important for disease diagnosis. However, existing methods not only ignore prior practical use but also observability entire system. Therefore, this paper proposes a new constrained multi-objective optimization-based temporal model (CMTNO) to identify biomarkers, which requires minimizing number selected nodes including ordinary and (the first optimization objective) maximizing second on premise...
Discrete diffusion models have emerged as a powerful generative modeling framework for discrete data with successful applications spanning from text generation to image synthesis. However, their deployment faces challenges due the high dimensionality of state space, necessitating development efficient inference algorithms. Current approaches mainly fall into two categories: exact simulation and approximate methods such $\tau$-leaping. While suffer unpredictable time redundant function...
Inspired by scaling laws and large language models, research on large-scale recommendation models has gained significant attention. Recent advancements have shown that expanding sequential to can be an effective strategy. Current state-of-the-art primarily use self-attention mechanisms for explicit feature interactions among items, while implicit are managed through Feed-Forward Networks (FFNs). However, these often inadequately integrate temporal positional information, either adding them...
Rapid ascent to high altitudes by unacclimatized individuals significantly increases the risk of brain damage, given brain’s heightened sensitivity hypoxic conditions. Investigating hypoxia-tolerant animals can provide insights into adaptive mechanisms and guide prevention treatment hypoxic-ischemic injury. In this study, we exposed Brandt’s voles simulated (100 m, 3000 5000 7000 m) for 24 h performed quantitative proteomic phosphoproteomic analyses tissue. A total 3990 proteins 9125...
Multiple driver genes in individual patient samples may cause resistance to drugs precision medicine. However, current computational methods have not studied how fill the gap between personalized gene identification and combinatorial drug discovery for patients. Here, we developed a novel structural network controllability-based algorithm (CPGD), aiming identify an by targeting from controllability perspective. On two benchmark disease datasets (i.e. breast cancer lung datasets), performance...
The advances in target control of complex networks not only can offer new insights into the general dynamics systems, but also be useful for practical application systems biology, such as discovering therapeutic targets disease intervention. In many cases, e.g. drug identification biological networks, we usually require a on subset nodes (i.e., disease-associated genes) with minimum cost, and further expect that more driver consistent certain well-selected network prior-known drug-target...
It is of great theoretical interest and practical significance to study how control a system by applying perturbations only few driver nodes. Recently, hot topic modern network researches determine nodes that allow the an entire network. However, in practice, complex network, especially biological one may know not set which need be controlled (i.e. target nodes), but also signals can applied constrained nodes). Compared general concept controllability, we introduce controllability (CTC)...
In the past few years, a wealth of sample-specific network construction methods and structural control has been proposed to identify driver nodes for supporting Sample-Specific Control (SSC) analysis biological networked systems. However, there is no comprehensive evaluation these state-of-the-art methods. Here, we conducted performance assessment 16 SSC workflows by using combination 4 reconstruction representative This study includes simulation networks, personalized genes prioritization...