DataSheet1_Mathematical algorithm–based identification of the functional components and mechanisms in depression treatment: An example of Danggui-Shaoyao-San.docx حسب Wenxia Gong (13277883)

الموضوعات: "…Cell Biology…"

Cost functions implemented in Neuroptimus. حسب Máté Mohácsi (20469514)

Supplementary Tables from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors حسب Xinyi Liu (20493753)

Supplementary Figure S2 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors حسب Xinyi Liu (20493753)

Supplementary Figure S7 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors حسب Xinyi Liu (20493753)

Supplementary Figure S6 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors حسب Xinyi Liu (20493753)

Supplementary Figure S5 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors حسب Xinyi Liu (20493753)

Supplementary Figure S8 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors حسب Xinyi Liu (20493753)

Supplementary Figure S1 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors حسب Xinyi Liu (20493753)

Supplementary Figure S4 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors حسب Xinyi Liu (20493753)

Supplementary Figure S9 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors حسب Xinyi Liu (20493753)

Supplementary Figure S3 from SpatialDeX Is a Reference-Free Method for Cell-Type Deconvolution of Spatial Transcriptomics Data in Solid Tumors حسب Xinyi Liu (20493753)

Comparison of scores obtained by our interpenetration and scoring algorithm (ISA) and ROSETTA for a subset of structures. حسب Kevin Sawade (16726527)

"…However, our algorithm was 1000 times faster than pyROSETTA (both algorithms have been parallelized on a per-structure basis using the Python package joblib [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010531#pcbi.1010531.ref069" target="_blank">69</a>]).…"

Table S2 from Precision Oncology beyond Targeted Therapy: Combining Omics Data with Machine Learning Matches the Majority of Cancer Cells to Effective Therapeutics حسب Michael Q. Ding (15079000)

Table S1 from Precision Oncology beyond Targeted Therapy: Combining Omics Data with Machine Learning Matches the Majority of Cancer Cells to Effective Therapeutics حسب Michael Q. Ding (15079000)

Table S3 from Precision Oncology beyond Targeted Therapy: Combining Omics Data with Machine Learning Matches the Majority of Cancer Cells to Effective Therapeutics حسب Michael Q. Ding (15079000)

Tabel S4 from Precision Oncology beyond Targeted Therapy: Combining Omics Data with Machine Learning Matches the Majority of Cancer Cells to Effective Therapeutics حسب Michael Q. Ding (15079000)

Implementation of the EMC² algorithm in Icy platform. حسب Thibault Lagache (492571)

The details of the Scelestial algorithm. حسب Mohammad-Hadi Foroughmand-Araabi (6658772)

"…<p>The inputs to the Scelestial algorithm are a) a set of sequences <i>S</i>, b) the degree of restriction of the restricted Steiner tree <i>k</i>. …"

Hybrid feature selection algorithm of CSCO-ROA. حسب Afnan M. Alhassan (18349378)

الموضوعات: "…Cell Biology…"