Ruedi H. Aebersold

Complex Assembly and Activity States as Multifaceted Protein Attributes Explaining Phenotypic Variability

The paper introduces a multi-omics framework to analyze protein activity in context-specific networks, demonstrating its utility in linking molecular profiles to phenotypic outcomes using HeLa and Kyoto cell lines.

Stringent proteogenomic discovery of novel small proteins in Mycobacterium tuberculosis clinical reference strains

The paper uses long-read assemblies and proteogenomic analysis to discover novel small proteins in Mycobacterium tuberculosis strains.

Drug-Prot: A query system for statistical inference of drug effects and interactions in dynamic proteomic networks

Drug-Prot quantifies drug effects and interactions using proteomic data, revealing protein-level causal relationships and actionable drug combinations.

Spatial distribution of the proteome in human body and cancers

The paper presents a comprehensive spatial proteome map of human tissues and cancers, enabling drug response analysis and target discovery.

Rv1985c-Driven Transcriptional Network Rewiring Underlies Lineage-Specific Phenotypes in Mycobacterium tuberculosis

This study identifies lineage-specific transcriptional network rewiring in Mtb by analyzing proteomic and transcriptomic data from L1 and L2 strains, revealing key regulators like Rv1985c that drive phenotypic differences.

The Pgb1 locus controls glycogen aggregation in astrocytes of the aged hippocampus without impacting cognitive function

The paper identifies the Pgb1 locus as controlling glycogen aggregation in aged hippocampal astrocytes without affecting cognitive function.

An atlas of protein-protein associations of human tissues prioritizes candidate disease genes

The paper constructs a tissue-specific protein interaction atlas using proteomic data from 11 human tissues, identifying key drivers of inter-tissue variation and prioritizing disease genes in brain disorders.

Deep Domain Adversarial Neural Network for the Deconvolution of Cell Type Mixtures in Tissue Proteome Profiling

This paper introduces scpDeconv, a deep learning method for deconvolving cell type mixtures in proteomic data, showing improved performance across species and technologies.

DIP-MS: A novel ultra-deep interaction proteomics for the deconvolution of protein complexes

DIP-MS resolves protein complex isoforms using deep learning and mass spectrometry, revealing new subunits in human prefoldin complexes.

Principles of gene regulation quantitatively connect DNA to RNA and proteins in bacteria

This study quantifies how gene regulation in E. coli connects DNA to RNA and proteins under growth condition changes, revealing two principles governing protein allocation.

Large-scale changes of molecular network states explain complex traits

The paper identifies a central state transition in yeast molecular networks linked to PKA and TOR signaling, showing how genetic variants can cause global or local molecular changes affecting multiple cellular traits.

7q11.23 CNV alters protein synthesis and REST-mediated neuronal intrinsic excitability

This study investigates how 7q11.23 CNVs affect protein synthesis and neuronal excitability in neurodevelopmental disorders using patient-derived neurons and multi-omics approaches.

Novel biochemical, structural and systems insights into inflammatory signaling revealed by contextual interaction proteomics

The paper presents an integrated experimental and computational strategy to model protein-protein interactions in cellular context, applied to the TNF-receptor signaling complex.

Mechanotransduction coordinates extracellular matrix protein homeostasis promoting longevity in C. elegans

The paper identifies hemidesmosome-containing structures that mediate mechanotransduction to regulate ECM homeostasis and promote longevity in C. elegans.

Proteomic Dynamics of Breast Cancers Identifies Potential Therapeutic Protein Targets

This study identifies a 24-protein panel distinguishing TNBC from other breast cancers and shows proteomics improves drug sensitivity predictions.

scROSHI - robust supervised hierarchical identification of single cells

scROSHI identifies cell types without training data by using pre-existing gene sets and hierarchical relationships, outperforming methods in low-data and high-diversity scenarios.

Systematic dissection of phosphorylation-dependent YAP1 complex formation elucidates a key role for PTPN14 in Hippo signal integration

The paper develops an experimental strategy to link phosphorylation events with protein complex formation, revealing PTPN14's role in regulating YAP1's interaction with LATS1/2 kinases.

All driven by energy demand? Integrative comparison of metabolism of Enterococcus faecalis wildtype and a glutamine synthase mutant

This study compares the metabolic and proteomic adaptations of E. faecalis wildtype and a glutamine synthase mutant under varying pH conditions, revealing energy demand as the key factor in adaptation.

Rapid profiling of protein complex re-organization in perturbed systems

The paper presents a rapid workflow combining experimental and computational methods to profile protein complex re-organization in cellular states, showing distinct changes during differentiation and macrophage stimulation.

Multi-Omic Profiling of the Liver Across Diets and Age in a Diverse Mouse Population

The paper uses multi-omics data from mice to identify gene-environment-age interactions and causal molecular networks linked to longevity.

Integrative analysis allows a global and precise identification of functional miRNA target genes in mESCs

The paper identifies that only 6% of expressed genes are functionally regulated by miRNAs in mESCs using integrative analysis of transcriptome data and miRNA interaction predictions.

Systematic detection of functional proteoform groups from bottom-up proteomic datasets

This paper introduces a data-driven method to detect functional proteoform groups from bottom-up proteomic datasets, identifying state-specific proteoform groups linked to molecular mechanisms.

Towards a systematic characterization of protein complex function: a natural language processing and machine-learning framework

PCfun annotates protein complex function using natural language processing and machine learning, integrating word embeddings from PubMed Central articles with supervised and unsupervised methods.

Convergent network effects along the axis of gene expression during prostate cancer progression

The paper investigates how genomic alterations affect molecular networks in prostate cancer by integrating genomic, transcriptomic, and proteomic data from 105 samples, identifying a sub-network predictive of tumor aggressiveness and recurrence.

SECAT: Quantifying differential protein-protein interaction states by network-centric analysis

SECAT quantifies differential protein-protein interaction states across cellular states by analyzing PPI networks, showing improved scalability and effectiveness over previous methods.

SCIM: Universal Single-Cell Matching with Unpaired Feature Sets

SCIM matches single-cell measurements across technologies by learning a technology-invariant latent space and applying bipartite matching, achieving high accuracy in real-world datasets.

Systematic protein complex profiling and differential analysis from co-fractionation mass spectrometry data

The paper introduces PCprophet, a computational framework for identifying and analyzing protein complexes from co-fractionation mass spectrometry data across conditions.

DPHL: A pan-human protein mass spectrometry library for robust biomarker discovery using Data-Independent Acquisition and Parallel Reaction Monitoring

The paper introduces DPHL, a pan-human protein mass spectrometry library built using DIA and PRM, and demonstrates its utility in identifying differentially expressed proteins in prostate cancer and DLBCL.

Parallel accumulation - serial fragmentation combined with data-independent acquisition (diaPASEF): Bottom-up proteomics with near optimal ion usage

The paper introduces a new DIA scan mode that improves peptide precursor ion sampling and identification specificity using ion mobility, achieving high proteome coverage and accuracy.

A global screen for assembly state changes of the mitotic proteome by SEC-SWATH-MS

The paper quantifies proteome assembly state changes during mitosis using SEC-SWATH-MS and identifies new mitotic complex disassembly events.