Works (26)
Updated: April 9th, 2024 05:01
2024 article
Topological and geometric analysis of cell states in single-cell transcriptomic data
Huynh, T., & Cang, Z. (2024, April 7).
Source: ORCID
Added: April 8, 2024
2023 article
A mathematical method and software for spatially mapping intercellular communication
Cang, Z., & Nie, Q. (2023, January 24). NATURE METHODS, Vol. 1.
MeSH headings : Cell Communication; Software
TL;DR:
This work presents an optimal transport theory-based tool to infer cell–cell communication networks, spatial signaling directions and downstream targets in multicellular systems from spatial gene expression data.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, ORCID
Added: February 20, 2023
2023 journal article
AVIDA: An alternating method for visualizing and integrating data
JOURNAL OF COMPUTATIONAL SCIENCE, 68, 101998.
author keywords: Dimension reduction; Data integration; Multi-omics data
arxiv.org (repository)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, ORCID
Added: May 15, 2023
2023 article
Screening cell-cell communication in spatial transcriptomics via collective optimal transport
Cang, Z., Zhao, Y., Almet, A. A. A., Stabell, A., Ramos, R., Plikus, M. V. V., … Nie, Q. (2023, January 23). NATURE METHODS, Vol. 1.
MeSH headings : Humans; Transcriptome; Cell Communication / genetics; Gene Expression Profiling; Signal Transduction; Computer Simulation; Single-Cell Analysis
TL;DR:
This work presents COMMOT (COMMunication analysis by Optimal Transport) to infer CCC in spatial transcriptomics, which accounts for the competition between different ligand and receptor species as well as spatial distances between cells.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, ORCID
Added: March 13, 2023
2022 journal article
Deciphering tissue structure and function using spatial transcriptomics
Communications Biology.
MeSH headings : Transcriptome
TL;DR:
This work synthesize and review the key problems in analysis of ST data and methods that are currently applied, while also expanding on open questions and areas of future development.
(via Semantic Scholar)
Source: ORCID
Added: March 11, 2022
2022 journal article
Identifying multicellular spatiotemporal organization of cells with SpaceFlow
NATURE COMMUNICATIONS, 13(1).
MeSH headings : Humans; Transcriptome / genetics
TL;DR:
This study introduces SpaceFlow, which generates spatially-consistent low-dimensional embeddings by incorporating both expression similarity and spatial information using spatially regularized deep graph networks, and introduces a pseudo-Spatiotemporal Map that integrates the pseudotime concept with spatial locations of the cells to unravel spatiotem temporal patterns of cells.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science; OpenAlex)
Sources: Web Of Science, ORCID
Added: July 26, 2022
2022 article
Screening cell-cell communication in spatial transcriptomics via collective optimal transport
Cang, Z., Zhao, Y., Almet, A. A., Stabell, A., Ramos, R., Plikus, M., … Nie, Q. (2022, August 26).
TL;DR:
This work presents COMMOT to infer CCC in spatial transcriptomics, which accounts for the competition among different ligand and receptor species as well as spatial distances between cells, and introduces downstream analysis tools on spatial directionality of signalings and genes regulated by such signalings using machine learning models.
(via Semantic Scholar)
Source: ORCID
Added: May 18, 2023
2021 journal article
A multiscale model via single-cell transcriptomics reveals robust patterning mechanisms during early mammalian embryo development
PLOS Computational Biology, 17(3), e1008571.
Ed(s): D. Umulis
MeSH headings : Animals; Embryo, Mammalian / cytology; Embryo, Mammalian / metabolism; Embryo, Mammalian / physiology; Embryonic Development / genetics; Germ Layers / cytology; Germ Layers / metabolism; Germ Layers / physiology; Mice; Models, Biological; Single-Cell Analysis; Transcriptome / genetics
TL;DR:
This study provides a multiscale framework that incorporates single-cell gene expression datasets to analyze gene regulations, cell-cell communications, and physical interactions among cells in complex geometries at single- cell resolution, with direct application to late-stage development of embryogenesis.
(via Semantic Scholar)
Source: ORCID
Added: August 22, 2021
2021 journal article
Charge substitutions at the voltage-sensing module of domain III enhance actions of site-3 and site-4 toxins on an insect sodium channel
Insect Biochemistry and Molecular Biology, 137, 103625.
author keywords: Insect sodium channel; Scorpion alpha-toxin; Scorpion beta-toxin; Homology modeling; Mutagenesis; Electrophysiology
MeSH headings : Animals; Cnidarian Venoms / pharmacology; Drosophila melanogaster / drug effects; Drosophila melanogaster / genetics; Drosophila melanogaster / metabolism; Insect Proteins / genetics; Insect Proteins / metabolism; Oocytes / drug effects; Oocytes / metabolism; Scorpion Venoms / pharmacology; Sodium Channels / genetics; Sodium Channels / metabolism
TL;DR:
These results highlight the involvement of III-VSM in the actions of both site 3 and site 4 toxins, suggesting that charge reversing substitutions in III- VSM allosterically facilitate IIS4 or IVS4 voltage sensor trapping by these toxins.
(via Semantic Scholar)
Source: ORCID
Added: August 22, 2021
2021 journal article
DEEPsc: A Deep Learning-Based Map Connecting Single-Cell Transcriptomics and Spatial Imaging Data
Frontiers in Genetics, 12.
author keywords: spatial gene expression atlas; scRNA-seq data; spatial information imputation; deep learning; metric learning; comprehensive evaluation metric
TL;DR:
DEEPsc provides a data-adaptive tool to connect scRNA-seq datasets and spatial imaging datasets to analyze cell fate decisions and is compared with four existing methods on four biological systems to find that while DEEPsc has comparable accuracy to other methods, an improved balance between precision and robustness is achieved.
(via Semantic Scholar)
Source: ORCID
Added: August 22, 2021
2021 journal article
Single-cell transcriptomic analysis of zebrafish cranial neural crest reveals spatiotemporal regulation of lineage decisions during development
Cell Reports.
MeSH headings : Animals; Animals, Genetically Modified; Branchial Region / metabolism; Cell Communication; Cell Differentiation; Cell Lineage; Cell Movement; Cranial Nerves / metabolism; Embryo, Nonmammalian / metabolism; Gene Expression Profiling / methods; Gene Expression Regulation, Developmental; Neural Crest / metabolism; RNA-Seq; Signal Transduction; Single-Cell Analysis; Wnt Proteins / metabolism; Zebrafish / genetics; Zebrafish / metabolism; Zebrafish Proteins / genetics; Zebrafish Proteins / metabolism
TL;DR:
The results show that cranial NC cell lineages arise progressively and uncover a series of spatially restricted cell interactions likely to regulate such cell-fate decisions.
(via Semantic Scholar)
Source: ORCID
Added: December 22, 2021
2021 journal article
The landscape of cell–cell communication through single-cell transcriptomics
Current Opinion in Systems Biology.
author keywords: Cell-cell interactions; Cell signaling; Inference; Intercellular communi- cation; Ligand-receptor interactions; Signaling networks; Single-cell RNA-Seq; Spatial transcriptomics
TL;DR:
This review discusses the recent explosion of methods that have been developed to infer cell-cell communication from non-spatial and spatial single-cell transcriptomics, two promising technologies which have complementary strengths and limitations.
(via Semantic Scholar)
Source: ORCID
Added: August 22, 2021
2020 journal article
A review of mathematical representations of biomolecular data
Physical Chemistry Chemical Physics.
TL;DR:
This review focuses the performance analysis on protein-ligand binding predictions in this review although these methods have had tremendous success in many other applications, such as protein classification, virtual screening, and the predictions of solubility, solvation free energies, toxicity, partition coefficients, protein folding stability changes upon mutation.
(via Semantic Scholar)
Source: ORCID
Added: August 22, 2021
2020 journal article
A topology-based network tree for the prediction of protein–protein binding affinity changes following mutation
Nature Machine Intelligence.
TL;DR:
Tests indicate that the proposed topology-based network tree is an important improvement over the current state of the art in predicting ΔΔG, and a new deep learning algorithm called NetTree is proposed to take advantage of convolutional neural networks and gradient-boosting trees to improve predictions of protein–protein interactions.
(via Semantic Scholar)
Source: ORCID
Added: August 22, 2021
2020 journal article
Defining Epidermal Basal Cell States during Skin Homeostasis and Wound Healing Using Single-Cell Transcriptomics
Cell Reports, 30(11), 3932–3947.e6.
MeSH headings : Animals; Cell Movement / genetics; Epidermis / metabolism; Epidermis / pathology; Female; Gene Expression Profiling; Homeostasis / genetics; Inflammation / genetics; Inflammation / pathology; Mice, Inbred C57BL; Mice, Transgenic; Single-Cell Analysis; Up-Regulation / genetics; Wound Healing / genetics
TL;DR:
This study provides a systematic view of epidermal cellular dynamics supporting a revised “hierarchical-lineage” model of homeostasis.
(via Semantic Scholar)
Source: ORCID
Added: August 22, 2021
2020 journal article
Evolutionary homology on coupled dynamical systems with applications to protein flexibility analysis
Journal of Applied and Computational Topology, 4(4), 481–507.
TL;DR:
Numerical results for the B-factor prediction of a benchmark set of 364 proteins indicate that the proposed evolutionary homology (EH) outperforms all the other state-of-the-art methods in the field.
(via Semantic Scholar)
Source: ORCID
Added: August 22, 2021
2020 journal article
Inferring spatial and signaling relationships between cells from single cell transcriptomic data
Nature Communications.
MeSH headings : Animals; Cell Communication; Cluster Analysis; Databases, Genetic; Drosophila / embryology; Drosophila / genetics; Gene Expression Regulation, Developmental; Reproducibility of Results; Sequence Analysis, RNA; Signal Transduction / genetics; Single-Cell Analysis; Transcriptome / genetics; Visual Cortex / metabolism; Zebrafish / embryology; Zebrafish / genetics
TL;DR:
An unbalanced and structured optimal transport method is applied to infer spatial and signalling relationships between cells from scRNA-seq data by integrating it with spatial imaging data.
(via Semantic Scholar)
Source: ORCID
Added: August 22, 2021
2020 journal article
Persistent Cohomology for Data With Multicomponent Heterogeneous Information
SIAM Journal on Mathematics of Data Science, 2(2), 396–418.
author keywords: topological data analysis; machine learning; biophysics; drug design
TL;DR:
It is found that the proposed framework outperforms or at least matches the state-of-the-art methods in the protein-ligand binding affinity prediction from massive biomolecular datasets without resorting to any deep learning formulation.
(via Semantic Scholar)
Source: ORCID
Added: August 22, 2021
2020 journal article
Structural cavities are critical to balancing stability and activity of a membrane-integral enzyme
Proceedings of the National Academy of Sciences, 117(36), 22146–22156.
author keywords: membrane protein stability; cavity; packing; GIpG; steric trapping
MeSH headings : Catalytic Domain; DNA-Binding Proteins / chemistry; DNA-Binding Proteins / metabolism; Endopeptidases / chemistry; Endopeptidases / metabolism; Escherichia coli Proteins / chemistry; Escherichia coli Proteins / metabolism; Humans; Membrane Proteins / chemistry; Membrane Proteins / metabolism; Models, Molecular; Molecular Dynamics Simulation; Mutation; Protein Conformation; Protein Folding; Protein Stability; Serine Endopeptidases / chemistry
TL;DR:
Using experiment and molecular dynamics simulation, it is shown that cavities in membrane proteins can be stabilized by favorable interaction with surrounding lipid molecules and play a pivotal role in balancing stability and flexibility for function.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
6. Clean Water and Sanitation
(OpenAlex)
Source: ORCID
Added: August 22, 2021
2019 journal article
Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges
Journal of Computer-Aided Molecular Design, 33(1), 71–82.
author keywords: Drug design; Pose prediction; Binding affinity; Machine learning; Algebraic topology; Graph theory
MeSH headings : Binding Sites; Cathepsins / chemistry; Computer-Aided Design; Crystallography, X-Ray; Databases, Protein; Deep Learning; Drug Design; Ligands; Molecular Docking Simulation / methods; Protein Binding; Protein Conformation; Protein Kinases / chemistry; Receptors, Cytoplasmic and Nuclear / chemistry; Thermodynamics
TL;DR:
The authors' models obtained the top place in absolute free energy prediction for free energy set 1 in stage 2 and were ranked 1st in 10 out of 26 official competitive tasks for GC3.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy
(OpenAlex)
Source: ORCID
Added: August 22, 2021
2018 journal article
Integration of element specific persistent homology and machine learning for protein‐ligand binding affinity prediction
International Journal for Numerical Methods in Biomedical Engineering.
author keywords: protein-ligand binding affinity; machine learning; topology
MeSH headings : Databases, Protein; Hydrogen Bonding; Ligands; Machine Learning; Protein Binding; Proteins / chemistry; Proteins / metabolism
TL;DR:
The present approach reveals that protein‐ligand hydrophobic interactions are extended to 40Å away from the binding site, which has a significant ramification to drug and protein design.
(via Semantic Scholar)
Source: ORCID
Added: August 22, 2021
2018 journal article
Protein pocket detection via convex hull surface evolution and associated Reeb graph
Bioinformatics, 34(17), i830–i837.
MeSH headings : Algorithms; Binding Sites; Ligands; Protein Binding; Protein Conformation; Proteins / chemistry; Software
TL;DR:
Extensive numerical tests indicate that the proposed method not only provides a unique description of pocket‐sub‐pocket relations, but also offers efficient estimations of pocket surface area, pocket volume and pocket depth.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(OpenAlex)
Source: ORCID
Added: August 22, 2021
2018 journal article
Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening
PLOS Computational Biology, 14(1), e1005929.
Ed(s): J. Peng
MeSH headings : Algorithms; Area Under Curve; Computational Biology / methods; Databases, Protein; Humans; Ligands; Machine Learning; Models, Neurological; Molecular Dynamics Simulation; Neural Networks, Computer; Nucleic Acids / chemistry; Protein Binding; Protein Interaction Mapping; Proteins / chemistry; Static Electricity
TL;DR:
It is demonstrated that the present topological learning outperforms other existing methods in protein-ligand binding affinity prediction and ligand-decoy discrimination.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
10. Reduced Inequalities
(OpenAlex)
Source: ORCID
Added: August 22, 2021
2017 journal article
Analysis and prediction of protein folding energy changes upon mutation by element specific persistent homology
Bioinformatics, 7.
MeSH headings : Algorithms; Computational Biology / methods; Mutagenesis; Mutation / physiology; Protein Folding; Protein Stability; Proteins / chemistry; Proteins / genetics; Proteins / metabolism; Software; Structural Homology, Protein; Thermodynamics
TL;DR:
The present approach is found to outperform other existing methods in the predictions of globular protein stability changes upon mutation, and has a 84% higher Pearson correlation coefficient than the current state‐of‐the‐art empirical methods.
(via Semantic Scholar)
Source: ORCID
Added: August 22, 2021
2017 journal article
TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions
PLOS Computational Biology, 13(7), e1005690.
Ed(s): R. Dunbrack
MeSH headings : Computational Biology / methods; Image Processing, Computer-Assisted; Machine Learning; Membrane Proteins / chemistry; Membrane Proteins / metabolism; Membrane Proteins / physiology; Models, Statistical; Molecular Dynamics Simulation; Neural Networks, Computer; Protein Binding; Protein Folding
TL;DR:
A multi-task multichannel topological convolutional neural network (MM-TCNN) that outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein foldingfree energy changes, and mutation induced membrane protein folding free energy changes.
(via Semantic Scholar)
Source: ORCID
Added: August 22, 2021
2015 journal article
A topological approach for protein classification
Computational and Mathematical Biophysics, 3(1).
TL;DR:
The present study establishes computational topology as an independent and effective alternative for protein classification as well as proposing a molecular topological fingerprint based support vector machine (MTF-SVM) classifier.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
10. Reduced Inequalities
(OpenAlex)
Source: ORCID
Added: August 22, 2021
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