Geng Tian
YOU?
Author Swipe
View article: MCLRP: enhanced prediction of anticancer drug response through low-rank matrix completion and transcriptomic profiling
MCLRP: enhanced prediction of anticancer drug response through low-rank matrix completion and transcriptomic profiling Open
Background Accurate prediction of anticancer drug responses remains a significant challenge due to the intricate interplay between genomic features and pharmacological mechanisms. We present Matrix Completion with Low-rank Regularization a…
View article: A comprehensive analysis of transcription factors identified TCF3 as a prognostic target for glioma
A comprehensive analysis of transcription factors identified TCF3 as a prognostic target for glioma Open
Transcription factors (TFs) are pivotal in tumor initiation and progression, regulating downstream gene expression and modulating cellular processes. In this study, we conducted a comprehensive analysis of TF gene sets to define the molecu…
View article: Dynamic mapping from static labels: remote sensing dynamic sample generation with temporal-spectral embedding
Dynamic mapping from static labels: remote sensing dynamic sample generation with temporal-spectral embedding Open
Accurate remote sensing geographic mapping requires timely and representative samples. However, rapid land surface changes often render static samples obsolete within months, making manual sample updates labor-intensive and unsustainable. …
View article: MMsurv: a multimodal multi-instance multi-cancer survival prediction model integrating pathological images, clinical information, and sequencing data
MMsurv: a multimodal multi-instance multi-cancer survival prediction model integrating pathological images, clinical information, and sequencing data Open
Accurate prediction of patient survival rates in cancer treatment is essential for effective therapeutic planning. Unfortunately, current models often underutilize the extensive multimodal data available, affecting confidence in prediction…
View article: ScMicrobesAtlas: A comprehensive microbial atlas at single-cell resolution in human disease contexts
ScMicrobesAtlas: A comprehensive microbial atlas at single-cell resolution in human disease contexts Open
View article: Integrated multi-omics analyses reveal causal insights into the molecular landscape of urologic cancers
Integrated multi-omics analyses reveal causal insights into the molecular landscape of urologic cancers Open
Background Urologic cancers continue to present an ongoing challenge to human health, underscoring the necessity for a systematic exploration of their underlying mechanisms. Hence, we employed a multi-omics Mendelian randomization (MR) app…
View article: Clinical study, network pharmacology, and molecular docking of Kunxian capsule in treating idiopathic membranous nephropathy
Clinical study, network pharmacology, and molecular docking of Kunxian capsule in treating idiopathic membranous nephropathy Open
Objective A new Tripterygium wilfordii preparation called Kunxian capsule (KX) has been approved in China. However, it is still unknown whether KX is safe and effective for idiopathic membranous nephropathy (IMN) and its therapeutic mechan…
View article: CAMIL: channel attention-based multiple instance learning for whole slide image classification
CAMIL: channel attention-based multiple instance learning for whole slide image classification Open
Motivation The classification task based on whole-slide images (WSIs) is a classic problem in computational pathology. Multiple instance learning (MIL) provides a robust framework for analyzing whole slide images with slide-level labels at…
View article: Genetic analyses identify circulating genes related to brain structures associated with Parkinson’s disease
Genetic analyses identify circulating genes related to brain structures associated with Parkinson’s disease Open
Magnetic resonance imaging and circulating molecular testing are potential methods for diagnosing and treating Parkinson's disease (PD). However, their relationships remain insufficiently studied. Using genome-wide association summary stat…
View article: Using Diffusion Models for Reducing Spatiotemporal Errors of Deep Learning Based Urban Microclimate Predictions at Post-Processing Stage
Using Diffusion Models for Reducing Spatiotemporal Errors of Deep Learning Based Urban Microclimate Predictions at Post-Processing Stage Open
Computational fluid dynamics (CFD) is a powerful tool for modeling turbulent flow and is commonly used for urban microclimate simulations. However, traditional CFD methods are computationally intensive, requiring substantial hardware resou…
View article: Dynamic mapping from static labels: remote sensing dynamic sample generation with temporal-spectral embedding
Dynamic mapping from static labels: remote sensing dynamic sample generation with temporal-spectral embedding Open
View article: Unveiling patterns in spatial transcriptomics data: a novel approach utilizing graph attention autoencoder and multiscale deep subspace clustering network
Unveiling patterns in spatial transcriptomics data: a novel approach utilizing graph attention autoencoder and multiscale deep subspace clustering network Open
Background The accurate deciphering of spatial domains, along with the identification of differentially expressed genes and the inference of cellular trajectory based on spatial transcriptomic (ST) data, holds significant potential for enh…
View article: ScLineageAtlas: a comprehensive single-cell genomics database for characterizing cellular clones in cancer
ScLineageAtlas: a comprehensive single-cell genomics database for characterizing cellular clones in cancer Open
Accurate identification of clonal relationships between cell populations is crucial for investigating cellular differentiation trajectories and gaining insights into the underlying mechanisms of cancer initiation and development. The Singl…
View article: Modern hit-finding with structure-guided de novo design: identification of novel nanomolar adenosine A2A receptor ligands using reinforcement learning
Modern hit-finding with structure-guided de novo design: identification of novel nanomolar adenosine A2A receptor ligands using reinforcement learning Open
Generative chemical language models have demonstrated success in learning language-based molecular representations for de novo drug design. Here, we integrate structure-based drug design (SBDD) principles with chemical language models to p…
View article: Modern hit-finding with structure-guided de novo design: identification of novel nanomolar A2A receptor ligands using reinforcement learning
Modern hit-finding with structure-guided de novo design: identification of novel nanomolar A2A receptor ligands using reinforcement learning Open
Generative chemical language models have demonstrated success in learning language-based molecular representations for de novo drug design. Here, we integrate structure-based design principles with chemical language models to present a mod…
View article: Development of a Multimodal Deep Learning Model for Predicting Microsatellite Instability in Colorectal Cancer by Integrating Histopathological Images and Clinical Data
Development of a Multimodal Deep Learning Model for Predicting Microsatellite Instability in Colorectal Cancer by Integrating Histopathological Images and Clinical Data Open
Microsatellite instability (MSI) arises from defective DNA mismatch repair (MMR) systems and is prevalent in various cancer types. MSI is classified as MSI-High (MSI-H), MSI-Low (MSI-L), or Microsatellite Stable (MSS), with the latter two …
View article: Analysis of High-Order Bright–Dark Rogue Waves in (2+1)-D Variable-Coefficient Zakharov Equation via Self-Similar and Darboux Transformations
Analysis of High-Order Bright–Dark Rogue Waves in (2+1)-D Variable-Coefficient Zakharov Equation via Self-Similar and Darboux Transformations Open
This paper conducts an in-depth study on the self-similar transformation, Darboux transformation, and the excitation and propagation characteristics of high-order bright–dark rogue wave solutions in the (2+1)-dimensional variable-coefficie…
View article: Explainable ensemble learning method for OCT detection with transfer learning
Explainable ensemble learning method for OCT detection with transfer learning Open
The accuracy and interpretability of artificial intelligence (AI) are crucial for the advancement of optical coherence tomography (OCT) image detection, as it can greatly reduce the manual labor required by clinicians. By prioritizing thes…
View article: A Pathology-Interpretable Deep Learning Model for Predicting Microsatellite Instability State in Colorectal Cancer: Validation across Diverse Platforms and Asian Cohorts
A Pathology-Interpretable Deep Learning Model for Predicting Microsatellite Instability State in Colorectal Cancer: Validation across Diverse Platforms and Asian Cohorts Open
Background The determination of microsatellite (MS) state plays a vital role in precise diagnosis and treatment of colorectal cancer (CRC). However, the limited availability of medical resources and challenging economic circumstances rende…
View article: Drug repositioning based on weighted local information augmented graph neural network
Drug repositioning based on weighted local information augmented graph neural network Open
Drug repositioning, the strategy of redirecting existing drugs to new therapeutic purposes, is pivotal in accelerating drug discovery. While many studies have engaged in modeling complex drug–disease associations, they often overlook the r…
View article: LDA-VGHB: identifying potential lncRNA–disease associations with singular value decomposition, variational graph auto-encoder and heterogeneous Newton boosting machine
LDA-VGHB: identifying potential lncRNA–disease associations with singular value decomposition, variational graph auto-encoder and heterogeneous Newton boosting machine Open
Long noncoding RNAs (lncRNAs) participate in various biological processes and have close linkages with diseases. In vivo and in vitro experiments have validated many associations between lncRNAs and diseases. However, biological experiment…
View article: Semi-relativistic antisymmetrized molecular dynamics for energetic neutron production in intermediate energy heavy-ion reactions
Semi-relativistic antisymmetrized molecular dynamics for energetic neutron production in intermediate energy heavy-ion reactions Open
Relativistic corrections have been made in the non-relativistic antisymmetrized molecular dynamics (AMD) simulations to apply to the high energy neutron production in the $^{12}$C+$^{12}$C and $^{16}$O+$^{12}$C collisions at incident energ…
View article: Predicting potential microbe-disease associations with graph attention autoencoder, positive-unlabeled learning, and deep neural network
Predicting potential microbe-disease associations with graph attention autoencoder, positive-unlabeled learning, and deep neural network Open
Background Microbes have dense linkages with human diseases. Balanced microorganisms protect human body against physiological disorders while unbalanced ones may cause diseases. Thus, identification of potential associations between microb…
View article: A cross-cohort computational framework to trace tumor tissue-of-origin based on RNA sequencing
A cross-cohort computational framework to trace tumor tissue-of-origin based on RNA sequencing Open
Carcinoma of unknown primary (CUP) is a type of metastatic cancer with tissue-of-origin (TOO) unidentifiable by traditional methods. CUP patients typically have poor prognosis but therapy targeting the original cancer tissue can significan…
View article: MicroEXPERT: Microbiome profiling platform with cross‐study metagenome‐wide association analysis functionality
MicroEXPERT: Microbiome profiling platform with cross‐study metagenome‐wide association analysis functionality Open
The framework of the MicroEXPERT platform. Our Platform was composed of five modules. Data management module: Users upload raw data and metadata to the system using a guided workflow. Data processing module: Uploaded data is processed to g…
View article: Molecular characterization of colorectal adenoma and colorectal cancer via integrated genomic transcriptomic analysis
Molecular characterization of colorectal adenoma and colorectal cancer via integrated genomic transcriptomic analysis Open
Introduction Colorectal adenoma can develop into colorectal cancer. Determining the risk of tumorigenesis in colorectal adenoma would be critical for avoiding the development of colorectal cancer; however, genomic features that could help …
View article: A cross-cohort computational framework to trace tumor tissue-of-origin based on RNA sequencing
A cross-cohort computational framework to trace tumor tissue-of-origin based on RNA sequencing Open
Carcinoma of unknown primary (CUP) is a type of metastatic cancer with tissue-of-origin (TOO) unidentifiable by traditional methods. CUP patients typically have poor prognosis but therapy targeting the original cancer tissue can significan…
View article: Emvirus: An embedding-based neural framework for human-virus protein-protein interactions prediction
Emvirus: An embedding-based neural framework for human-virus protein-protein interactions prediction Open
View article: Intratumoral Microbiota-Host Interactions Shape the Variability of Lung Adenocarcinoma and Lung Squamous Cell Carcinoma in Recurrence and Metastasis
Intratumoral Microbiota-Host Interactions Shape the Variability of Lung Adenocarcinoma and Lung Squamous Cell Carcinoma in Recurrence and Metastasis Open
Our study elucidates significant differences in RM-associated host-microbe interactions between LUAD and LUSC. Besides, the microbes in tumor tissue could be used to predict the RM risk of LUSC, and the predicted risk score is associated w…
View article: Graph Convolutional Neural Network for Predicting the Associations among Human Microbes and Diseases via Multi-layer Attention
Graph Convolutional Neural Network for Predicting the Associations among Human Microbes and Diseases via Multi-layer Attention Open
Various microorganisms are affinitive with the pathogenesis of Human-related diseases and have become new targets for disease therapy. Since the limitations of long development period and high development funds for the wet-lab validation o…