S.-H. Shiu

Evolution of research topics and paradigms in plant sciences

The paper uses machine learning and language models to analyze plant science citations and track the evolution of research topics and paradigms over 50 years.

Temporal Regulation of Cold Transcriptional Response in Switchgrass

The paper identifies cis-regulatory elements in switchgrass that regulate cold-responsive gene expression over time using machine learning on transcriptome data.

The SEEL Motif and Members of the MYB-related REVEILLE Transcription Factor Family are Important for the Expression of LORELEI in the Synergid Cells of the Arabidopsis Female Gametophyte

Genome-wide predictions of genetic redundancy in Arabidopsis thaliana

This study develops a machine learning model to predict genetic redundancy in Arabidopsis thaliana using diverse features, identifying key predictors like recent duplication and stress-related expression.

Modeling gene regulation in response to wounding: temporal variations, hormonal variations, and specialized metabolism pathways induced by wounding

The paper models gene regulation in plants after wounding using machine learning, identifying cis-regulatory elements and showing their role in temporal and hormonal responses.

Optimizing the use of gene expression data to predict plant metabolic pathway memberships

This study predicts plant metabolic pathway memberships using gene expression data and machine learning, finding that unsupervised learning and expression similarity outperform naive methods in some cases.

Evolutionary analysis of the LORELEI gene family in angiosperms reveals regulatory subfunctionalization

The paper investigates LLG gene family evolution in angiosperms and finds expression divergence, not functional divergence, explains retention of paralogs in Brassicales.

Evolution of a plant gene cluster in Solanaceae and emergence of metabolic diversity

The paper studies the evolution of a gene cluster in Solanaceae plants and its role in producing medium chain acylsugars through trichome-specific enzymes.

Within and cross species predictions of plant specialized metabolism genes using transfer learning

The paper uses transfer learning to predict specialized metabolism genes in tomato by leveraging annotations from Arabidopsis thaliana, improving prediction accuracy.

Putative cis-regulatory elements predict iron deficiency responses in Arabidopsis roots

The paper identifies 100 putative cis-regulatory elements that predict Arabidopsis root responses to iron deficiency using computational analysis of genome and transcriptome data.

Cis-regulatory code for predicting plant cell-type specific high salinity response

The paper identifies cis-regulatory elements in Arabidopsis root cell types that predict high salinity gene responses and shows their effectiveness compared to in vitro transcription factor data.

Robust predictions of specialized metabolism genes through machine learning

The paper develops a machine learning model to predict specialized metabolism genes in Arabidopsis thaliana by integrating multiple genomic features, achieving high accuracy in identification.

Factors influencing gene family size variation among related species in a plant family

The paper investigates gene family size variation in Solanaceae species, finding relationships between gene function, duplication mechanisms, and evolutionary rates.

Regulatory Divergence In Wound-Responsive Gene Expression In Domesticated And Wild Tomato

This study identifies cis- and trans-regulatory divergence in wound-responsive gene expression between wild and domesticated tomato species.