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non-branching pseudodynamics model  (MathWorks Inc)


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    MathWorks Inc non-branching pseudodynamics model
    (A) Diagramatic representation of megakaryocyte trajectory analysis with <t>pseudodynamics.</t> Following the arrows: putative cell transitions (pseudotime kernel) were used to estimate megakaryocyte cell fate, from which megakaryocyte trajectory was isolated (dashed line). Along the pseudotime cell densities were computed for each time-point (color-coded density profiles) and analyzed using the pseudodynamics framework providing differentiation and net proliferation rate estimates for each cell. (B) (left) UMAP projection of the HSPC landscape color- coded by cell fate probability of neutrophil lineage (estimated with pseudotime kernel, see A). Panels on the right show UMAP projections of isolated neutrophil trajectory color-coded by indicated parameters or gene expression. (C) Pseudodynamics fitted net proliferation parameter (red) and differentiation rate parameters (blue) along pseudotime for megakaryocyte trajectory. Vertical lines indicate the region of interest. (D) Heatmap of genes differentially expressed around the region of interest shown in C. Left columns indicate genes belonging to enriched gene categories - E2F target (FDR <10 -38 ), G2-M checkpoint (FDR <10 -24 ) and cell cycle (FDR <10 -38 ). (E) Pseudodynamics fitted net proliferation (red) and differentiation rate (blue) parameters along pseudotime for neutrophil trajectory. Vertical lines indicate the region of interest. (F) Fitted gene expression values along pseudotime for neutrophil markers and two TF groups shown in (full analysis in ). Grey, dashed line indicated differentiation rates shown in E. Gene expression was scaled around the mean.
    Non Branching Pseudodynamics Model, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/non-branching pseudodynamics model/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    non-branching pseudodynamics model - by Bioz Stars, 2026-03
    90/100 stars

    Images

    1) Product Images from "A time and single-cell resolved model of hematopoiesis"

    Article Title: A time and single-cell resolved model of hematopoiesis

    Journal: bioRxiv

    doi: 10.1101/2022.09.07.506735

    (A) Diagramatic representation of megakaryocyte trajectory analysis with pseudodynamics. Following the arrows: putative cell transitions (pseudotime kernel) were used to estimate megakaryocyte cell fate, from which megakaryocyte trajectory was isolated (dashed line). Along the pseudotime cell densities were computed for each time-point (color-coded density profiles) and analyzed using the pseudodynamics framework providing differentiation and net proliferation rate estimates for each cell. (B) (left) UMAP projection of the HSPC landscape color- coded by cell fate probability of neutrophil lineage (estimated with pseudotime kernel, see A). Panels on the right show UMAP projections of isolated neutrophil trajectory color-coded by indicated parameters or gene expression. (C) Pseudodynamics fitted net proliferation parameter (red) and differentiation rate parameters (blue) along pseudotime for megakaryocyte trajectory. Vertical lines indicate the region of interest. (D) Heatmap of genes differentially expressed around the region of interest shown in C. Left columns indicate genes belonging to enriched gene categories - E2F target (FDR <10 -38 ), G2-M checkpoint (FDR <10 -24 ) and cell cycle (FDR <10 -38 ). (E) Pseudodynamics fitted net proliferation (red) and differentiation rate (blue) parameters along pseudotime for neutrophil trajectory. Vertical lines indicate the region of interest. (F) Fitted gene expression values along pseudotime for neutrophil markers and two TF groups shown in (full analysis in ). Grey, dashed line indicated differentiation rates shown in E. Gene expression was scaled around the mean.
    Figure Legend Snippet: (A) Diagramatic representation of megakaryocyte trajectory analysis with pseudodynamics. Following the arrows: putative cell transitions (pseudotime kernel) were used to estimate megakaryocyte cell fate, from which megakaryocyte trajectory was isolated (dashed line). Along the pseudotime cell densities were computed for each time-point (color-coded density profiles) and analyzed using the pseudodynamics framework providing differentiation and net proliferation rate estimates for each cell. (B) (left) UMAP projection of the HSPC landscape color- coded by cell fate probability of neutrophil lineage (estimated with pseudotime kernel, see A). Panels on the right show UMAP projections of isolated neutrophil trajectory color-coded by indicated parameters or gene expression. (C) Pseudodynamics fitted net proliferation parameter (red) and differentiation rate parameters (blue) along pseudotime for megakaryocyte trajectory. Vertical lines indicate the region of interest. (D) Heatmap of genes differentially expressed around the region of interest shown in C. Left columns indicate genes belonging to enriched gene categories - E2F target (FDR <10 -38 ), G2-M checkpoint (FDR <10 -24 ) and cell cycle (FDR <10 -38 ). (E) Pseudodynamics fitted net proliferation (red) and differentiation rate (blue) parameters along pseudotime for neutrophil trajectory. Vertical lines indicate the region of interest. (F) Fitted gene expression values along pseudotime for neutrophil markers and two TF groups shown in (full analysis in ). Grey, dashed line indicated differentiation rates shown in E. Gene expression was scaled around the mean.

    Techniques Used: Isolation, Gene Expression

    (A) UMAP projections of the HSPC landscape color-coded by cell fate probability for respective lineages (estimated with pseudotime kernel). (B) UMAP projections with cells selected for respective trajectories color-coded in blue. (C) Pseudodynamics fitted net proliferation and differentiation rate parameters along pseudotime for the megakaryocyte trajectory. Vertical lines indicate the region of interest. (D) Heatmap of TFs differentially expressed around the region of interest shown in C. (E) Pseudodynamics fitted net proliferation and differentiation rate parameters along pseudotime for the erythroid trajectory. Vertical lines indicate the region of interest. (F) Heatmap of TFs differentially expressed around the region of interest shown in E. (G) Pseudodynamics fitted net proliferation and differentiation rate parameters along pseudotime for the monocyte/dendritic cell trajectory. Vertical lines indicate the region of interest. (H) Heatmap of TFs differentially expressed around the region of interest shown in G.
    Figure Legend Snippet: (A) UMAP projections of the HSPC landscape color-coded by cell fate probability for respective lineages (estimated with pseudotime kernel). (B) UMAP projections with cells selected for respective trajectories color-coded in blue. (C) Pseudodynamics fitted net proliferation and differentiation rate parameters along pseudotime for the megakaryocyte trajectory. Vertical lines indicate the region of interest. (D) Heatmap of TFs differentially expressed around the region of interest shown in C. (E) Pseudodynamics fitted net proliferation and differentiation rate parameters along pseudotime for the erythroid trajectory. Vertical lines indicate the region of interest. (F) Heatmap of TFs differentially expressed around the region of interest shown in E. (G) Pseudodynamics fitted net proliferation and differentiation rate parameters along pseudotime for the monocyte/dendritic cell trajectory. Vertical lines indicate the region of interest. (H) Heatmap of TFs differentially expressed around the region of interest shown in G.

    Techniques Used:



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    non-branching pseudodynamics model  (MathWorks Inc)
    90
    MathWorks Inc non-branching pseudodynamics model
    (A) Diagramatic representation of megakaryocyte trajectory analysis with <t>pseudodynamics.</t> Following the arrows: putative cell transitions (pseudotime kernel) were used to estimate megakaryocyte cell fate, from which megakaryocyte trajectory was isolated (dashed line). Along the pseudotime cell densities were computed for each time-point (color-coded density profiles) and analyzed using the pseudodynamics framework providing differentiation and net proliferation rate estimates for each cell. (B) (left) UMAP projection of the HSPC landscape color- coded by cell fate probability of neutrophil lineage (estimated with pseudotime kernel, see A). Panels on the right show UMAP projections of isolated neutrophil trajectory color-coded by indicated parameters or gene expression. (C) Pseudodynamics fitted net proliferation parameter (red) and differentiation rate parameters (blue) along pseudotime for megakaryocyte trajectory. Vertical lines indicate the region of interest. (D) Heatmap of genes differentially expressed around the region of interest shown in C. Left columns indicate genes belonging to enriched gene categories - E2F target (FDR <10 -38 ), G2-M checkpoint (FDR <10 -24 ) and cell cycle (FDR <10 -38 ). (E) Pseudodynamics fitted net proliferation (red) and differentiation rate (blue) parameters along pseudotime for neutrophil trajectory. Vertical lines indicate the region of interest. (F) Fitted gene expression values along pseudotime for neutrophil markers and two TF groups shown in (full analysis in ). Grey, dashed line indicated differentiation rates shown in E. Gene expression was scaled around the mean.
    Non Branching Pseudodynamics Model, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/non-branching pseudodynamics model/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    non-branching pseudodynamics model - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    (A) Diagramatic representation of megakaryocyte trajectory analysis with pseudodynamics. Following the arrows: putative cell transitions (pseudotime kernel) were used to estimate megakaryocyte cell fate, from which megakaryocyte trajectory was isolated (dashed line). Along the pseudotime cell densities were computed for each time-point (color-coded density profiles) and analyzed using the pseudodynamics framework providing differentiation and net proliferation rate estimates for each cell. (B) (left) UMAP projection of the HSPC landscape color- coded by cell fate probability of neutrophil lineage (estimated with pseudotime kernel, see A). Panels on the right show UMAP projections of isolated neutrophil trajectory color-coded by indicated parameters or gene expression. (C) Pseudodynamics fitted net proliferation parameter (red) and differentiation rate parameters (blue) along pseudotime for megakaryocyte trajectory. Vertical lines indicate the region of interest. (D) Heatmap of genes differentially expressed around the region of interest shown in C. Left columns indicate genes belonging to enriched gene categories - E2F target (FDR <10 -38 ), G2-M checkpoint (FDR <10 -24 ) and cell cycle (FDR <10 -38 ). (E) Pseudodynamics fitted net proliferation (red) and differentiation rate (blue) parameters along pseudotime for neutrophil trajectory. Vertical lines indicate the region of interest. (F) Fitted gene expression values along pseudotime for neutrophil markers and two TF groups shown in (full analysis in ). Grey, dashed line indicated differentiation rates shown in E. Gene expression was scaled around the mean.

    Journal: bioRxiv

    Article Title: A time and single-cell resolved model of hematopoiesis

    doi: 10.1101/2022.09.07.506735

    Figure Lengend Snippet: (A) Diagramatic representation of megakaryocyte trajectory analysis with pseudodynamics. Following the arrows: putative cell transitions (pseudotime kernel) were used to estimate megakaryocyte cell fate, from which megakaryocyte trajectory was isolated (dashed line). Along the pseudotime cell densities were computed for each time-point (color-coded density profiles) and analyzed using the pseudodynamics framework providing differentiation and net proliferation rate estimates for each cell. (B) (left) UMAP projection of the HSPC landscape color- coded by cell fate probability of neutrophil lineage (estimated with pseudotime kernel, see A). Panels on the right show UMAP projections of isolated neutrophil trajectory color-coded by indicated parameters or gene expression. (C) Pseudodynamics fitted net proliferation parameter (red) and differentiation rate parameters (blue) along pseudotime for megakaryocyte trajectory. Vertical lines indicate the region of interest. (D) Heatmap of genes differentially expressed around the region of interest shown in C. Left columns indicate genes belonging to enriched gene categories - E2F target (FDR <10 -38 ), G2-M checkpoint (FDR <10 -24 ) and cell cycle (FDR <10 -38 ). (E) Pseudodynamics fitted net proliferation (red) and differentiation rate (blue) parameters along pseudotime for neutrophil trajectory. Vertical lines indicate the region of interest. (F) Fitted gene expression values along pseudotime for neutrophil markers and two TF groups shown in (full analysis in ). Grey, dashed line indicated differentiation rates shown in E. Gene expression was scaled around the mean.

    Article Snippet: To solve the PDE, we used the non-branching pseudodynamics model as compiled in MATLAB 2017b, with only one difference: we did not enforce differentiation to be 0 at the end of the trajectory which, together with the growth rates taking also negative values, accounts for the fact that the populations in our landscape are all transient and that fully mature cells are not captured by our gating strategy.

    Techniques: Isolation, Gene Expression

    (A) UMAP projections of the HSPC landscape color-coded by cell fate probability for respective lineages (estimated with pseudotime kernel). (B) UMAP projections with cells selected for respective trajectories color-coded in blue. (C) Pseudodynamics fitted net proliferation and differentiation rate parameters along pseudotime for the megakaryocyte trajectory. Vertical lines indicate the region of interest. (D) Heatmap of TFs differentially expressed around the region of interest shown in C. (E) Pseudodynamics fitted net proliferation and differentiation rate parameters along pseudotime for the erythroid trajectory. Vertical lines indicate the region of interest. (F) Heatmap of TFs differentially expressed around the region of interest shown in E. (G) Pseudodynamics fitted net proliferation and differentiation rate parameters along pseudotime for the monocyte/dendritic cell trajectory. Vertical lines indicate the region of interest. (H) Heatmap of TFs differentially expressed around the region of interest shown in G.

    Journal: bioRxiv

    Article Title: A time and single-cell resolved model of hematopoiesis

    doi: 10.1101/2022.09.07.506735

    Figure Lengend Snippet: (A) UMAP projections of the HSPC landscape color-coded by cell fate probability for respective lineages (estimated with pseudotime kernel). (B) UMAP projections with cells selected for respective trajectories color-coded in blue. (C) Pseudodynamics fitted net proliferation and differentiation rate parameters along pseudotime for the megakaryocyte trajectory. Vertical lines indicate the region of interest. (D) Heatmap of TFs differentially expressed around the region of interest shown in C. (E) Pseudodynamics fitted net proliferation and differentiation rate parameters along pseudotime for the erythroid trajectory. Vertical lines indicate the region of interest. (F) Heatmap of TFs differentially expressed around the region of interest shown in E. (G) Pseudodynamics fitted net proliferation and differentiation rate parameters along pseudotime for the monocyte/dendritic cell trajectory. Vertical lines indicate the region of interest. (H) Heatmap of TFs differentially expressed around the region of interest shown in G.

    Article Snippet: To solve the PDE, we used the non-branching pseudodynamics model as compiled in MATLAB 2017b, with only one difference: we did not enforce differentiation to be 0 at the end of the trajectory which, together with the growth rates taking also negative values, accounts for the fact that the populations in our landscape are all transient and that fully mature cells are not captured by our gating strategy.

    Techniques: