Kosuke Ogata

This study shows that HBV BCP mutations enhance viral replication and alter hepatocyte transcription, linking to specific HCC subtypes.

The paper identifies phosphorylation sites that regulate protein interactions using pan-cancer data and AlphaFold predictions, revealing 6,160 associations between phosphosites and interacting protein abundance.

This paper introduces a method to detect protein conformational changes on a proteome-wide scale using kinase-mediated phosphorylation and phosphoproteomics.

The paper develops predictors to functionally characterize human phosphosites using integrated data, revealing novel functions and connections to DNA repair and cell survival.

This paper evaluates two SDB-containing PTFE disks for proteomics, finding one provides better peptide recovery, especially for low-input samples.

This study demonstrates that protease type XIII from Aspergillus saitoi improves bottom-up proteomics under acidic conditions by enhancing sequence coverage and reducing modification artifacts compared to trypsin.

UniScore integrates and standardizes outputs from multiple search engines in proteomics, outperforming single search engines in large-scale data analysis.

The paper introduces a pretrained deep protein language model for predicting peptide collision cross sections, reducing training time while maintaining or improving prediction performance.

This paper introduces a desalting tip column (ChocoTip) that improves peptide recovery in proteomics, outperforming existing methods in sensitivity and coverage.

This study develops a timing-controllable m6A demethylation tool with reduced off-target effects by combining PUF RNA-binding proteins with m6A-erasers and a rapamycin-based switch.

The paper develops a protein half-life prediction model, PLTNUM, using a protein language model trained on NIH3T3 mouse data, achieving 71% accuracy and identifying key sequence features affecting half-life.

This paper develops a high-speed LC/MS/MS system achieving 1,000 samples per day with high sensitivity and depth, demonstrating its application in spatial proteomics of mouse brain.

The paper introduces a motif-centric phosphoproteomics approach to quantify phosphorylation pathways using in vitro kinase reactions and isobaric labeling, demonstrating selective quantification of over 7,000 tyrosine phosphorylation sites.

The paper develops a sequence-specific model to predict peptide collision cross-section values using amino-acid sequence and charge state information from proteomic data.