AIMC Topic: Proteomics
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A Plasma Proteomics-Based Model for Identifying the Risk of Postpartum Depression Using Machine Learning.
Journal of proteome research
Jan 7, 2025
Postpartum depression (PPD) poses significant risks to maternal and infant health, yet proteomic analyses of PPD-risk women remain limited. This study analyzed plasma samples from 30 healthy postpartum women and 30 PPD-risk women using mass spectrome...
π-PrimeNovo: an accurate and efficient non-autoregressive deep learning model for de novo peptide sequencing.
Nature communications
Jan 2, 2025
Peptide sequencing via tandem mass spectrometry (MS/MS) is essential in proteomics. Unlike traditional database searches, deep learning excels at de novo peptide sequencing, even for peptides missing from existing databases. Current deep learning mod...
Identifying proteomic prognostic markers for Alzheimer's disease with survival machine learning: The Framingham Heart Study.
The journal of prevention of Alzheimer's disease
Jan 1, 2025
BACKGROUND: Protein abundance levels, sensitive to both physiological changes and external interventions, are useful for assessing the Alzheimer's disease (AD) risk and treatment efficacy. However, identifying proteomic prognostic markers for AD is c...
NovoRank: Refinement for Peptide Sequencing Based on Spectral Clustering and Deep Learning.
Journal of proteome research
Dec 31, 2024
peptide sequencing is a valuable technique in mass-spectrometry-based proteomics, as it deduces peptide sequences directly from tandem mass spectra without relying on sequence databases. This database-independent method, however, relies solely on im...
ViroNia: LSTM based proteomics model for precise prediction of HCV.
Computers in biology and medicine
Dec 29, 2024
Classification of viruses carries important implications in terms of understanding their evolution and the designing of interventions. This study introduces ViroNia as a novel LSTM-based system specifically meant for high-accuracy classification of v...
Proteome profiling of cerebrospinal fluid using machine learning shows a unique protein signature associated with APOE4 genotype.
Aging cell
Dec 25, 2024
Proteome changes associated with APOE4 variant carriage that are independent of Alzheimer's disease (AD) pathology and diagnosis are unknown. This study investigated APOE4 proteome changes in people with AD, mild cognitive impairment, and no impairme...
DFASGCNS: A prognostic model for ovarian cancer prediction based on dual fusion channels and stacked graph convolution.
PloS one
Dec 16, 2024
Ovarian cancer is a malignant tumor with different clinicopathological and molecular characteristics. Due to its nonspecific early symptoms, the majority of patients are diagnosed with local or extensive metastasis, severely affecting treatment and p...
DeepPD: A Deep Learning Method for Predicting Peptide Detectability Based on Multi-feature Representation and Information Bottleneck.
Interdisciplinary sciences, computational life sciences
Dec 11, 2024
Peptide detectability measures the relationship between the protein composition and abundance in the sample and the peptides identified during the analytical procedure. This relationship has significant implications for the fundamental tasks of prote...
Mapping the functional network of human cancer through machine learning and pan-cancer proteogenomics.
Nature cancer
Dec 11, 2024
Large-scale omics profiling has uncovered a vast array of somatic mutations and cancer-associated proteins, posing substantial challenges for their functional interpretation. Here we present a network-based approach centered on FunMap, a pan-cancer f...
Subtyping strokes using blood-based protein biomarkers: A high-throughput proteomics and machine learning approach.
European journal of clinical investigation
Dec 10, 2024
BACKGROUND: Rapid diagnosis of stroke and its subtypes is critical in early stages. We aimed to discover and validate blood-based protein biomarkers to differentiate ischemic stroke (IS) from intracerebral haemorrhage (ICH) using high-throughput prot...
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