Search alternatives:
codon optimization » wolf optimization (Expand Search)
cell optimization » field optimization (Expand Search), wolf optimization (Expand Search), lead optimization (Expand Search)
binary basic » binary mask (Expand Search)
basic codon » basic column (Expand Search)
lines red » lines used (Expand Search), times red (Expand Search), lines e (Expand Search)
red cell » 3d cell (Expand Search), d cell (Expand Search)
Showing 1 - 20 results of 73 for search '(( binary basic codon optimization algorithm ) OR ( lines red cell optimization algorithm ))', query time: 0.39s Refine Results
  1. 1
    Graphic representation of the CAP A events identified by the algorithm (blue line) and by the scorer (red line).

    Graphic representation of the CAP A events identified by the algorithm (blue line) and by the scorer (red line). by Maria Paola Tramonti Fantozzi (11785619)

    Published 2021
    Save to List
    Saved in:
  2. 2
    Example medication days generated for patients P4 and P6, medication times (red dots), patient’s state—TRS score (blue line) with bounds for the states (red lines) and optimal state (green line).

    Example medication days generated for patients P4 and P6, medication times (red dots), patient’s state—TRS score (blue line) with bounds for the states (red lines) and optimal stat... by Tomasz Gutowski (17200042)

    Published 2023
    Save to List
    Saved in:
  3. 3
    Violin plots of the distributions of the parameter values not shown in Fig 3 for the model cells included in the analysis, normalized over the range of allowed variability of each parameter (black and red indicate thorny and a-thorny cells, respectively).

    Violin plots of the distributions of the parameter values not shown in Fig 3 for the model cells included in the analysis, normalized over the range of allowed variability of each... by Daniele Linaro (227790)

    Published 2022
    Save to List
    Saved in:
  4. 4
    Highly sensitive conductance parameters are well-constrained by the optimized calibration pipeline.

    Highly sensitive conductance parameters are well-constrained by the optimized calibration pipeline. by Janice Yang (5747246)

    Published 2024
    Save to List
    Saved in:
  5. 5
    Firing patterns of a-thorny cells encode more information about the statistics of presynaptic inputs.

    Firing patterns of a-thorny cells encode more information about the statistics of presynaptic inputs. by Daniele Linaro (227790)

    Published 2022
    Save to List
    Saved in:
  6. 6
    Graphic representation of the adapted Ferri’s algorithm.

    Graphic representation of the adapted Ferri’s algorithm. by Maria Paola Tramonti Fantozzi (11785619)

    Published 2021
    Save to List
    Saved in:
  7. 7
    Instance-paired data of leave-one-out validation of segmentation algorithm in CC.

    Instance-paired data of leave-one-out validation of segmentation algorithm in CC. by Philip Ruthig (22097312)

    Published 2025
    Save to List
    Saved in:
  8. 8
    Instance-paired data of leave-one-out validation of segmentation algorithm in SWM.

    Instance-paired data of leave-one-out validation of segmentation algorithm in SWM. by Philip Ruthig (22097312)

    Published 2025
    Save to List
    Saved in:
  9. 9
    Optimized calibration protocol can generate models that predict I<sub>K1</sub> block response, despite fitting to normalized data without amplitude information.

    Optimized calibration protocol can generate models that predict I<sub>K1</sub> block response, despite fitting to normalized data without amplitude information. by Janice Yang (5747246)

    Published 2024
    Save to List
    Saved in:
  10. 10
    A mid-sagittal view of a lumbar spine MRI showing the intersection lines between the sagittal plane and the traverse planes that are shown in Fig 3.

    A mid-sagittal view of a lumbar spine MRI showing the intersection lines between the sagittal plane and the traverse planes that are shown in Fig 3. by Friska Natalia (9592260)

    Published 2022
    Save to List
    Saved in:
  11. 11
    Evolution of optimal search behaviour in Act cells is subject to constraints and trade-offs.

    Evolution of optimal search behaviour in Act cells is subject to constraints and trade-offs. by Inge M. N. Wortel (12085952)

    Published 2023
    Save to List
    Saved in:
  12. 12
    Fig 14 -

    Fig 14 - by Masashi Yagi (3186909)

    Published 2023
    Save to List
    Saved in:
  13. 13
    Fig 8 -

    Fig 8 - by Masashi Yagi (3186909)

    Published 2023
    Save to List
    Saved in:
  14. 14
    Fig 11 -

    Fig 11 - by Masashi Yagi (3186909)

    Published 2023
    Save to List
    Saved in:
  15. 15
    Fig 9 -

    Fig 9 - by Masashi Yagi (3186909)

    Published 2023
    Save to List
    Saved in:
  16. 16
    Fig 6 -

    Fig 6 - by Masashi Yagi (3186909)

    Published 2023
    Save to List
    Saved in:
  17. 17
    Fig 10 -

    Fig 10 - by Masashi Yagi (3186909)

    Published 2023
    Save to List
    Saved in:
  18. 18
    Fig 5 -

    Fig 5 - by Masashi Yagi (3186909)

    Published 2023
    Save to List
    Saved in:
  19. 19
    Fig 13 -

    Fig 13 - by Masashi Yagi (3186909)

    Published 2023
    Save to List
    Saved in:
  20. 20
    Distributions of model parameters mirror differentially expressed ion channel genes.

    Distributions of model parameters mirror differentially expressed ion channel genes. by Daniele Linaro (227790)

    Published 2022
    Save to List
    Saved in:

Search Tools: