A5116548940- Genomics and Phylogenetic Studies
- vaccines and immunoinformatics approaches
- Single-cell and spatial transcriptomics
- Gene expression and cancer classification
- Genomics and Chromatin Dynamics
- Advanced Proteomics Techniques and Applications
- Machine Learning in Bioinformatics
- Immunotherapy and Immune Responses
- Extracellular vesicles in disease
- RNA and protein synthesis mechanisms
- Cell Image Analysis Techniques
- Surface and Thin Film Phenomena
- Advanced Physical and Chemical Molecular Interactions
- Mass Spectrometry Techniques and Applications
- Pharmacovigilance and Adverse Drug Reactions
- Metabolomics and Mass Spectrometry Studies
- International Arbitration and Investment Law
- Genetic Mapping and Diversity in Plants and Animals
- Thermodynamic and Structural Properties of Metals and Alloys
- T-cell and B-cell Immunology
- RNA regulation and disease
- Protein Structure and Dynamics
- Isotope Analysis in Ecology
- RNA modifications and cancer
- Gene Regulatory Network Analysis
University of Waterloo
1977-2025
Central South University
2019
China University of Political Science and Law
2008
Recent advances in cellular research demonstrate that scRNA-seq characterizes heterogeneity, while spatial transcriptomics reveals the distribution of gene expression. Cell representation is fundamental issue two fields. Here, we propose Topology-encoded Latent Hyperbolic Geometry (TopoLa), a computational framework enhancing cell representations by capturing fine-grained intercellular topological relationships. The introduces new metric, TopoLa distance (TLd), which quantifies geometric...
Abstract The side effects of drugs present growing concern attention in the healthcare system. Accurately identifying is very important for drug development and risk assessment. Some computational models have been developed to predict potential provided satisfactory performance. However, most existing methods can only whether will occur cannot determine frequency effects. Although a few effects, they strongly depend on known drug-side effect relationships. Therefore, be applied new without...
Cancer remains a significant global health challenge, responsible for millions of deaths annually. Addressing this issue necessitates the discovery novel anti-cancer drugs. Anti-cancer peptides (ACPs), with their unique ability to selectively target cancer cells, offer new hope in discovering low side-effect However, process ACPs is both time-consuming and costly. Therefore, there an urgent need computational method that can predict whether given peptide ACP classify its specific functional...
Single-cell RNA sequencing (scRNA-seq) technologies have become essential tools for characterizing cellular landscapes within complex tissues. Large-scale single-cell transcriptomics holds great potential identifying rare cell types critical to the pathogenesis of diseases and biological processes. Existing methods often rely on one-time clustering using partial or global gene expression. However, these may be overlooked during phase, posing challenges their accurate identification. In this...
For pt.II see ibid., vol.5, p.1849 (1975). The use of an energy-independent model pseudopotential, developed using a low-order pseudopotential perturbation theory (see part I) is extended to (i) first-principles calculation second-order elastic constants and phonon spectra the alkali metals employing number widely used exchange-correlation factors, F(q), electron gas (ii) derivation more reliable expression for electrical resistivities solid simple metals. Then, authors consider possible...
Abstract Summary The recent advance in genome engineering technologies based on CRISPR/Cas9 system is enabling people to systematically understand genomic functions. A short RNA string (the CRISPR guide RNA) can the Cas9 endonuclease specific locations complex genomes cut DNA double-strands. essential for gene editing systems. Recently, GuideScan software developed design libraries, which be used of coding and non-coding regions effectively. However, a serial program computationally...
Abstract Single-cell RNA sequencing (scRNA-seq) technologies have been widely used to characterize cellular landscapes in complex tissues. Large-scale single-cell transcriptomics holds great potential for identifying rare cell types critical the pathogenesis of diseases and biological processes. Existing methods often rely on one-time clustering using partial or global gene expression. However, these may be overlooked initial step, making them difficult distinguish. In this paper, we propose...
The aim of deconvolution top-down mass spectra is to recognize monoisotopic peaks from the experimental envelopes in raw spectra. So accurate assessment similarity between theoretical and a critical step data deconvolution. Existing evaluation methods primarily rely on intensity differences
Major Histocompatibility Complex (MHC) molecules play a critical role in the immune system by presenting peptides on cell surface for recognition T-cells. Tumor cells often produce MHC with amino acid mutations, known as neoantigens, which evade T-cell recognition, leading to rapid tumor growth. In immunotherapies such TCR-T and CAR-T, identifying these mutated peptide sequences is crucial. Current mass spectrometry-based identification methods primarily rely database searching, fails detect...
<title>Abstract</title> Differential high-order chromatin interactions between homologous chromosomes play pivotal roles in many biological processes. However, their elucidation has been hindered by technical difficulties. Traditional 3C methods mainly expose 2-way and offer limited haplotype information. In response, we addressed challenges harnessing merely nanopore concatemer (Pore-C) reads to delineate diploid interactions. By training a cutting-edge deep learning model making...
Abstract In diploid organisms, spatial variations between homologous chromosomes are essential to many biological phenomena. Currently, it is still challenging efficiently reconstruct a high-quality 3D human genome. Here, we introduce Dip3D, reconstructing the genome using Pore-C data of one sample. Dip3D has solved multiple problems in genome-wide SNV calling and haplo-tagging caused by high sequencing error rates type data. capitalizes on high-order chromosomal interaction characteristics,...
Amyloid light chain (AL) amyloidosis is a disorder characterized by the deposition of antibody chains in organs. Early and accurate diagnosis AL crucial for timely implementation appropriate treatment strategies. However, existing computational methods predicting often heavily rely on manually extracted features their performance less than satisfactory. In this study, we introduce DeepAL, deep learning-based approach designed to predict with high precision. DeepAL utilizes pre-trained model...