mass-spectrometry

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#mass-spectrometry

The ovary doesn't retire after menopause

Hacker News Top ↗ · 2026-10-18 Cached

A Northwestern University and Buck Institute study published in Aging Cell finds that postmenopausal ovaries remain biologically active, continuing to remodel with age and sharing molecular profiles linked to ovarian cancer, challenging long-held assumptions about the ovary after menopause.

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#mass-spectrometry

Critical Mass: Structure-Disjoint Splits Drift With the Libraries They Are Built On

arXiv cs.LG ↗ · 2026-10-12 Cached

论文提出优化的 MCES 距离计算方法,使结构不相交的数据集划分可在大规模分子库上可行,并发现 MassSpecGym 等基准中单一连通分量占库的 95.5%,导致测试集系统性地偏向更大更复杂的分子,混淆了结构新颖性与外推难度。

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#mass-spectrometry

Nearest-neighbour baselines for fingerprint prediction from MS/MS spectra under different assumptions

arXiv cs.LG ↗ · 2026-10-05 Cached

该预印本系统比较了在不同推理信息假设(无化学式、已知化学式、峰值带子式注释)下的最近邻基线方法,用于从MS/MS光谱预测分子指纹,评估了五种谱相似度在NPLIB1与MassSpecGym数据集上的表现。

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#mass-spectrometry

GyroNovo: Error-Guided Fragment Imputation with Mass-Aware Attention for \textit{De Novo} Peptide Sequencing

arXiv cs.LG ↗ · 2026-09-29 Cached

GyroNovo improves de novo peptide sequencing by adaptively imputing missing fragments based on decoder errors and incorporating mass differences via rotary embeddings, achieving state-of-the-art performance on benchmarks.

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#mass-spectrometry

Predicting Collision Cross Sections with GRACE: Geometric Residual Adduct Conditioning via Early-fusion

arXiv cs.LG ↗ · 2026-09-14 Cached

GRACE is a novel 3D predictor for collision cross sections in ion mobility mass spectrometry, using geometric residual adduct conditioning via early fusion to improve accuracy and generalization.

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#mass-spectrometry

Scientists unlock secrets of ancient Egyptian materials with proteomics

Ars Technica ↗ · 2026-09-11 Cached

Scientists used mass spectrometry-based proteomics to analyze ancient Egyptian artifacts, discovering the use of animal-derived proteins like cow glue in adhesives and paints.

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#mass-spectrometry

Biologically Informed Representation Learning for Robust Cross-Center Generalization of MALDI-TOF Mass Spectrometry

arXiv cs.LG ↗ · 2026-08-11 Cached

Introduces DALMA, a probabilistic representation learning framework that uses biological supervision to improve cross-center generalization of MALDI-TOF mass spectrometry models for clinical microbiology tasks like microbial identification and antimicrobial resistance prediction.

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