Tianshou Zhou
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View article: Meta-Analysis and Topological Perturbation in Interactomic Network for Antiopioid Addiction Drug Repurposing
Meta-Analysis and Topological Perturbation in Interactomic Network for Antiopioid Addiction Drug Repurposing Open
The ongoing opioid crisis highlights the urgent need for novel therapeutic strategies that can be rapidly deployed. This study presents a novel approach to identify potential repurposable drugs for the treatment of opioid addiction, aiming…
View article: Machine learning predictions from unpredictable chaos
Machine learning predictions from unpredictable chaos Open
Chaos is omnipresent in nature, and its understanding provides enormous social and economic benefits. However, the unpredictability of chaotic systems is a textbook concept due to their sensitivity to initial conditions, aperiodic behaviou…
View article: High-resolution and large-stretch single photon-gated sampling of chaotic laser
High-resolution and large-stretch single photon-gated sampling of chaotic laser Open
Achieving high-fidelity acquisition and reconstruction of chaotic signals at a single-photon level remains a key challenge in secure communication and ultrasensitive sensing, primarily due to bandwidth and resolution limits of single-photo…
View article: Proteomic Learning of Gamma-Aminobutyric Acid (GABA) Receptor-Mediated Anesthesia
Proteomic Learning of Gamma-Aminobutyric Acid (GABA) Receptor-Mediated Anesthesia Open
Anesthetics are crucial in surgical procedures and therapeutic interventions, but they come with side effects and varying levels of effectiveness, calling for novel anesthetic agents that offer more precise and controllable effects. Target…
View article: Late‐Onset Krabbe Disease: Case Report of Two Patients in a Chinese Family and Literature Review
Late‐Onset Krabbe Disease: Case Report of Two Patients in a Chinese Family and Literature Review Open
Background Krabbe disease (KD; globoid cell leucodystrophy) is a rare autosomal recessive lipid storage disorder that affects the white matter of the peripheral and central nervous. Late‐onset KD is less frequently diagnosed and often pres…
View article: Diffusive topology preserving manifold distances for single-cell data analysis
Diffusive topology preserving manifold distances for single-cell data analysis Open
Manifold learning techniques have emerged as crucial tools for uncovering latent patterns in high-dimensional single-cell data. However, most existing dimensionality reduction methods primarily rely on 2D visualization, which can distort t…
View article: Deciphering HIV-1 Transcription Initiation and Elongation from Single-Molecule Imaging Data
Deciphering HIV-1 Transcription Initiation and Elongation from Single-Molecule Imaging Data Open
The stages of transcription initiation and elongation are critical in the regulation of HIV-1 gene expression. Recent single-molecule imaging in living cells has shown that HIV-1 transcription occurs across multiple time scales and plays a…
View article: A review of machine learning methods for imbalanced data challenges in chemistry
A review of machine learning methods for imbalanced data challenges in chemistry Open
Imbalanced data, where certain classes are significantly underrepresented in a dataset, is a widespread machine learning (ML) challenge across various fields of chemistry, yet it remains inadequately addressed.
View article: Marker genes reveal dynamic features of cell evolving processes
Marker genes reveal dynamic features of cell evolving processes Open
Motivation Embryonic cells finally evolve into various types of mature cells, where cell fate determinations play pivotal roles, but dynamic features of this process remain elusive. Results We analyze four single-cell RNA sequencing datase…
View article: Exact burst-size distributions for gene-expression models with complex promoter structure
Exact burst-size distributions for gene-expression models with complex promoter structure Open
In prokaryotic and eukaryotic cells, most genes are transcribed in a bursty fashion on one hand and complex gene regulations may lead to complex promoter structure on the other hand. This raises an unsolved issue: how does promoter structu…
View article: Transformer technology in molecular science
Transformer technology in molecular science Open
A transformer is the foundational architecture behind large language models designed to handle sequential data by using mechanisms of self‐attention to weigh the importance of different elements, enabling efficient processing and understan…
View article: Reconstructing the evolution history of networked complex systems
Reconstructing the evolution history of networked complex systems Open
The evolution processes of complex systems carry key information in the systems’ functional properties. Applying machine learning algorithms, we demonstrate that the historical formation process of various networked complex systems can be …
View article: Reconstructing the evolution history of networked complex systems
Reconstructing the evolution history of networked complex systems Open
The evolution processes of complex systems carry key information in the systems' functional properties. Applying machine learning algorithms, we demonstrate that the historical formation process of various networked complex systems can be …
View article: Balanced implicit Patankar–Euler methods for positive solutions of stochastic differential equations of biological regulatory systems
Balanced implicit Patankar–Euler methods for positive solutions of stochastic differential equations of biological regulatory systems Open
Stochastic differential equations (SDEs) are a powerful tool to model fluctuations and uncertainty in complex systems. Although numerical methods have been designed to simulate SDEs effectively, it is still problematic when numerical solut…
View article: Power-law behavior of transcriptional bursting regulated by enhancer–promoter communication
Power-law behavior of transcriptional bursting regulated by enhancer–promoter communication Open
Revealing how transcriptional bursting kinetics are genomically encoded is challenging because genome structures are stochastic at the organization level and are suggestively linked to gene transcription. To address this challenge, we deve…
View article: Nascent RNA kinetics with complex promoter architecture: Analytic results and parameter inference
Nascent RNA kinetics with complex promoter architecture: Analytic results and parameter inference Open
Transcription is a stochastic process that involves several downstream operations, which make it difficult to model and infer transcription kinetics from mature RNA numbers in individual cell. However, recent advances in single-cell techno…
View article: 4D nucleome equation predicts gene expression controlled by long-range enhancer-promoter interaction
4D nucleome equation predicts gene expression controlled by long-range enhancer-promoter interaction Open
Recent experimental evidence strongly supports that three-dimensional (3D) long-range enhancer-promoter (E-P) interactions have important influences on gene-expression dynamics, but it is unclear how the interaction information is translat…
View article: Machine learning study of the extended drug–target interaction network informed by pain related voltage-gated sodium channels
Machine learning study of the extended drug–target interaction network informed by pain related voltage-gated sodium channels Open
Pain is a significant global health issue, and the current treatment options for pain management have limitations in terms of effectiveness, side effects, and potential for addiction. There is a pressing need for improved pain treatments a…
View article: Composite Patankar-Euler methods for positive simulations of stochastic differential equation models for biological regulatory systems
Composite Patankar-Euler methods for positive simulations of stochastic differential equation models for biological regulatory systems Open
Stochastic differential equations (SDE) are a powerful tool to model biological regulatory processes with intrinsic and extrinsic noise. However, numerical simulations of SDE models may be problematic if the values of noise terms are negat…
View article: Supplementary Materials from A Spatio-Temporal Model of Macrophage-Mediated Drug Resistance in Glioma Immunotherapy
Supplementary Materials from A Spatio-Temporal Model of Macrophage-Mediated Drug Resistance in Glioma Immunotherapy Open
This Supplementary file includs Text S1-S6, Figure S1-S6 and Table S1-S2. Text S1:Dimensionless equations. Text S2: Radial symmetry simplification of the system. Text S3: Initial and boundary conditions. Text S4: Parameter estimation. Text…
View article: Data from A Spatio-Temporal Model of Macrophage-Mediated Drug Resistance in Glioma Immunotherapy
Data from A Spatio-Temporal Model of Macrophage-Mediated Drug Resistance in Glioma Immunotherapy Open
The emergence of drug resistance is often an inevitable obstacle that limits the long-term effectiveness of clinical cancer chemotherapeutics. Although various forms of cancer cell-intrinsic mechanisms of drug resistance have been experime…
View article: Supplementary Materials from A Spatio-Temporal Model of Macrophage-Mediated Drug Resistance in Glioma Immunotherapy
Supplementary Materials from A Spatio-Temporal Model of Macrophage-Mediated Drug Resistance in Glioma Immunotherapy Open
This Supplementary file includs Text S1-S6, Figure S1-S6 and Table S1-S2. Text S1:Dimensionless equations. Text S2: Radial symmetry simplification of the system. Text S3: Initial and boundary conditions. Text S4: Parameter estimation. Text…
View article: Data from A Spatio-Temporal Model of Macrophage-Mediated Drug Resistance in Glioma Immunotherapy
Data from A Spatio-Temporal Model of Macrophage-Mediated Drug Resistance in Glioma Immunotherapy Open
The emergence of drug resistance is often an inevitable obstacle that limits the long-term effectiveness of clinical cancer chemotherapeutics. Although various forms of cancer cell-intrinsic mechanisms of drug resistance have been experime…
View article: Inferring transcriptional bursting kinetics from single-cell snapshot data using a generalized telegraph model
Inferring transcriptional bursting kinetics from single-cell snapshot data using a generalized telegraph model Open
Gene expression has inherent stochasticity resulting from transcription's burst manners. Single-cell snapshot data can be exploited to rigorously infer transcriptional burst kinetics, using mathematical models as blueprints. The classical …