Weixiong Zhang

This study identifies shared brain states in MDD and healthy controls using resting-state fMRI and hidden Markov modeling, revealing two distinct neurodynamic architectures associated with different symptom patterns.

The paper introduces MBS, a multimodal scoring system to quantify depression-like severity in stressed mice, identifying resilient subpopulations and behavioral patterns across stress models.

The paper introduces circFormer, a genomic language model-driven method for circular RNA identification, which outperforms traditional approaches and validates a high percentage of its candidates.

The paper develops a neurocomputational framework to predict recurrence risk in first-episode depression using resting-state fMRI and identifies circuit-level neural correlates of relapse.

The paper constructs nearly T2T genomes and a pan-genome of cassava cultivars and wild ancestors, revealing domestication genes and evolutionary insights.

The paper identifies cancer-keeping genes (CKGs) as therapeutic targets by extending network structural controllability theory to bladder cancer and validates their cancer-suppressing effects through experiments.

The paper develops MNP DNA markers and MNP-Seq method for accurate and efficient genotyping, showing high polymorphism and accuracy in rice and cotton.

The paper introduces Maestro, a network analysis method that identifies synchronized genetic activities in Alzheimer's disease, finding a pattern associated with AD that is significantly more common in cases than controls.