Eric W. Deutsch

The paper creates a high-confidence human methylation atlas and develops a deep learning model for methylated peptide detection.

The paper identifies 25% of 7,264 non-canonical open reading frames (ncORFs) as producing translated gene products, supported by over 3,000 peptides from 3.8 billion mass spectra.

The paper presents the E. coli PeptideAtlas build, a comprehensive pan-proteome resource covering 4,755 proteins and over 10,000 PTM sites from 40 datasets.

The paper predicts novel phosphorylation sites across eukaryotes using conservation analysis and evaluates their functional relevance by linking conservation patterns to protein functions and kinase evolution.

The paper expands and refines a reference catalog of human non-canonical open reading frames (ncORFs) by incorporating more datasets and introducing a translation signature score framework to prioritize high-quality ncORFs.

PloverDB provides a platform to serve biomedical knowledge graphs as standards-compliant web APIs, enhancing data accessibility and interoperability.

The paper provides an updated Candida albicans PeptideAtlas proteomics resource with detailed PTM data and tools for analysis.

The paper assesses MS-based identifications of unannotated human microproteins, finding large variation in reported proteins and PSM quality across studies.

The paper develops a pan-gene catalogue for Asian cultivated rice by creating a reference panel of 16 cultivars and identifying core and cultivar-specific genes.

The paper identifies sulfotyrosine (sY) sites in the human phosphoproteome by distinguishing them from phosphorylation using mass error shifts and filters out false positives, finding 31 convincing sY sites.

This paper performs a meta-analysis of 11 phosphoproteomics datasets to identify phosphorylated sites in Plasmodium falciparum and related species, revealing sequence motifs, conservation patterns, and structural context of phosphosites.

This study analyzes rice phosphoproteomics data to identify phosphosite variations across the rice pan-genome and their functional implications.

This paper discusses the current state of research on non-canonical open reading frames (ORFs) and proposes standards for their investigation and reporting using Ribo-seq and proteomics.

ARAX is a graph-based reasoning tool that integrates knowledge across sources to answer translational biomedical questions.

RTX-KG2 integrates 70 biomedical knowledge sources into a standards-compliant knowledge graph with a Biolink schema, providing downloadable and queryable versions via API.

This paper outlines a community-driven initiative to create a consolidated catalog of human Ribo-seq ORFs, addressing the lack of standardized annotation for these features.

The paper evaluates consensus spectrum generation methods in proteomics, finding BEST and BIN to be the most reliable for peptide identification.

The paper estimates the false discovery rate of phosphosites in public databases and predicts a more realistic count of true phosphosites in the human proteome.

The paper introduces a method to independently estimate the false localisation rate in phosphoproteomics using decoy amino acids, showing that alanine and leucine provide reliable results.

The paper introduces a standardized metadata format for proteomics datasets to improve reusability and integration across public repositories.

The paper introduces the Universal Spectrum Identifier (USI) to standardize referencing mass spectra in proteomics repositories, enabling transparent traceability of spectral evidence in publications.

The paper introduces a web-based tool for cross-resource peptide spectrum comparison and visualization, with a focus on integration and retrieval from spectral databases.

The paper introduces mzMLb, a new mass spectrometry data format optimized for speed and storage, validated to outperform existing formats in performance and compatibility.

The paper updates the HPP MS Data Interpretation Guidelines to improve accuracy and address new workflows and data standards.

The paper provides considerations and recommendations for designing and analyzing plasma proteomics studies to improve translational applications in clinical settings.

PTMProphet provides localization confidence for post-translational modifications in proteomics data, improving accuracy for downstream analysis.

The paper introduces PEFF, a new format for proteomics data that enhances FASTA with metadata for sequence variants and PTMs, enabling better analysis in proteogenomics and top-down proteomics.

The paper presents tools for ensuring FAIRness in big biomedical data analysis through a case study on creating a transcription factor binding site atlas from ENCODE data.

The paper introduces a fast hashing method for comparing semi-structured data, demonstrating its use on electronic health records for duplicate detection and clustering.

BDQC identifies data outliers and anomalies in large-scale genomic pipelines without domain knowledge, improving data quality and enabling new insights.