DataSheet1_Stochastic and Iterative Based Optimization for Enhancing Dynamic Performance of Interconnected Power System With Hybrid Energy Storage.docx حسب Niveditha Sivadanam (12328148)

Example result of an ECAP measurement obtained from the FG-SNR algorithm within a stimulation range of 0 to 36 nC. حسب Lutz Gärtner (10515482)

Pulsed Blue Laser Diode Thermal Desorption Microplasma Imaging Mass Spectrometry حسب Alexander Knodel (8538882)

Adding a new function module. حسب Yukako Yamane (9034133)

Table_6_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_8_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_4_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_2_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_3_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_5_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_10_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_7_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_9_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Table_1_Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.XLSX حسب Shiqi Zhang (709298)

Framework for identifying essential anticancer genes. حسب Chao-Ting Cheng (15675292)

Preliminary model calibrations to in vitro data support findings from in silico calibrations. حسب Janice Yang (5747246)

Posture identification allows the tracking of other cells during late-stage embryogenesis. حسب Andrew Lauziere (14192836)

This Figure shows the flow of information between components when running a simulation. حسب Till Köster (11287803)

Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2‑Acylpyrrole Derivatives حسب Carlos Santiago (13227143)

"…A computational high-throughput screening (cHTS) study of 2-acylpyrroles <b>5a</b>,<b>b</b> has been performed calculating >20,700 activity scores <i>vs</i> a large space of 647 assays involving multiple <i>Leishmania</i> species, cell lines, and potential target proteins. Overall, the study demonstrates that the SOFT.PTML all-in-one strategy is useful to obtain IFPTML models in a friendly interface making the work easier and faster than before. …"

Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2‑Acylpyrrole Derivatives حسب Carlos Santiago (13227143)

"…A computational high-throughput screening (cHTS) study of 2-acylpyrroles <b>5a</b>,<b>b</b> has been performed calculating >20,700 activity scores <i>vs</i> a large space of 647 assays involving multiple <i>Leishmania</i> species, cell lines, and potential target proteins. Overall, the study demonstrates that the SOFT.PTML all-in-one strategy is useful to obtain IFPTML models in a friendly interface making the work easier and faster than before. …"