Shuang G. Zhao

Matching Patients With Cell Surface-Targeted Clinical Trials Using Large Language Models.

Clinical Utility of Transcriptomic Signatures to Identify Androgen Receptor and Neuroendocrine Signaling in Prostate Cancer.

Multi-Institutional Study Evaluating the Role of Early Circulating Tumor DNA Dynamics During Treatment With Immune Checkpoint Inhibitors in Patients With Advanced-Stage Melanoma.

OGDHL Promotes Prostate Cancer Progression and Regulates Neuroendocrine Marker Expression and Nucleotide Abundance.

Precision Diagnostics in Prostate Cancer Treatment (PREDICT): A Phase II Multiarm Biomarker-Based Study (Alliance A032102)

High-Purity CTC RNA Sequencing Identifies Prostate Cancer Lineage Phenotypes Prognostic for Clinical Outcomes

High-purity CTC RNA sequencing identifies prostate cancer lineage phenotypes prognostic for clinical outcomes.

Predicting dose response to prostate cancer radiotherapy: validation of a radiation signature in the randomized phase III NRG/RTOG 0126 and SAKK 09/10 trials

Analysis of cfDNA fragmentomics metrics and commercial targeted sequencing panels

The characterization of variable new antigen receptors targeting FAP isolated from a novel immunized library.

Analysis of cfDNA fragmentomics metrics and commercial targeted sequencing panels.

Identifying prognostic targets in metastatic prostate cancer beyond AR.

Hierarchical spatial attention Mamba network for predicting pathological complete response to neoadjuvant chemotherapy from breast DCE-MRI

Figure S9 from High-Purity CTC RNA Sequencing Identifies Prostate Cancer Lineage Phenotypes Prognostic for Clinical Outcomes

OGDHL regulates tumor growth, neuroendocrine marker expression, and nucleotide abundance in prostate cancer

Figure 6 from High-Purity CTC RNA Sequencing Identifies Prostate Cancer Lineage Phenotypes Prognostic for Clinical Outcomes

Figure S2 from High-Purity CTC RNA Sequencing Identifies Prostate Cancer Lineage Phenotypes Prognostic for Clinical Outcomes

Data from Expression and Therapeutic Targeting of TROP-2 in Treatment-Resistant Prostate Cancer

Figure S7 from High-Purity CTC RNA Sequencing Identifies Prostate Cancer Lineage Phenotypes Prognostic for Clinical Outcomes

Data from Intrinsic Molecular Subtypes of Metastatic Castration-Resistant Prostate Cancer

Figure S3 from Expression and Therapeutic Targeting of TROP-2 in Treatment-Resistant Prostate Cancer

Figure S8 from High-Purity CTC RNA Sequencing Identifies Prostate Cancer Lineage Phenotypes Prognostic for Clinical Outcomes

Supplementary Figure S1 from Intrinsic Molecular Subtypes of Metastatic Castration-Resistant Prostate Cancer

Live Cell Sorting of Differentiated Primary Human Osteoclasts Allows Generation of Transcriptomic Signature Matrix

Figure S4 from Expression and Therapeutic Targeting of TROP-2 in Treatment-Resistant Prostate Cancer

Table 1 from High-Purity CTC RNA Sequencing Identifies Prostate Cancer Lineage Phenotypes Prognostic for Clinical Outcomes

Figure S4 from High-Purity CTC RNA Sequencing Identifies Prostate Cancer Lineage Phenotypes Prognostic for Clinical Outcomes

Figure S6 from High-Purity CTC RNA Sequencing Identifies Prostate Cancer Lineage Phenotypes Prognostic for Clinical Outcomes

Figure S10 from High-Purity CTC RNA Sequencing Identifies Prostate Cancer Lineage Phenotypes Prognostic for Clinical Outcomes

Figure 5 from High-Purity CTC RNA Sequencing Identifies Prostate Cancer Lineage Phenotypes Prognostic for Clinical Outcomes

CAREER: Physics-Based Differentiable and Inverse Rendering

CAREER: Physics-Based Differentiable and Inverse Rendering

CHS: Medium: Collaborative Research: Physics and Learning Integration Using Differentiable Rendering

CHS: Small: Predictive Material Appearance Modeling at Multiple Scales