AIMC Topic: Computational Biology
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An exploration into CTEPH medications: Combining natural language processing, embedding learning, in vitro models, and real-world evidence for drug repurposing.
PLoS computational biology
Sep 12, 2024
BACKGROUND: In the modern era, the growth of scientific literature presents a daunting challenge for researchers to keep informed of advancements across multiple disciplines.
Accurately identifying positive and negative regulation of apoptosis using fusion features and machine learning methods.
Computational biology and chemistry
Sep 11, 2024
Apoptotic proteins play a crucial role in the apoptosis process, ensuring a balance between cell proliferation and death. Thus, further elucidating the regulatory mechanisms of apoptosis will enhance our understanding of their functions. However, the...
DeepDBS: Identification of DNA-binding sites in protein sequences by using deep representations and random forest.
Methods (San Diego, Calif.)
Sep 11, 2024
Interactions of biological molecules in organisms are considered to be primary factors for the lifecycle of that organism. Various important biological functions are dependent on such interactions and among different kinds of interactions, the protei...
Scaling data toward pan-cancer foundation models.
Trends in cancer
Sep 11, 2024
Recent advances in artificial intelligence (AI) have revolutionized computational pathology (CPath), particularly through deep learning (DL) and neural networks (NNs). In a recent study, Vorontsov et al. introduced Virchow, a new foundation model (FM...
A natural language processing system for the efficient extraction of cell markers.
Scientific reports
Sep 11, 2024
Single-cell RNA sequencing (scRNA-seq) has emerged as a pivotal tool for exploring cellular landscapes across diverse species and tissues. Precise annotation of cell types is essential for understanding these landscapes, relying heavily on empirical ...
AI-derived comparative assessment of the performance of pathogenicity prediction tools on missense variants of breast cancer genes.
Human genomics
Sep 11, 2024
Single nucleotide variants (SNVs) can exert substantial and extremely variable impacts on various cellular functions, making accurate predictions of their consequences challenging, albeit crucial especially in clinical settings such as in oncology. L...
Oscillations in an artificial neural network convert competing inputs into a temporal code.
PLoS computational biology
Sep 11, 2024
The field of computer vision has long drawn inspiration from neuroscientific studies of the human and non-human primate visual system. The development of convolutional neural networks (CNNs), for example, was informed by the properties of simple and ...
Aging-related biomarkers for the diagnosis of Parkinson's disease based on bioinformatics analysis and machine learning.
Aging
Sep 10, 2024
Parkinson's disease (PD) is a multifactorial disease that lacks reliable biomarkers for its diagnosis. It is now clear that aging is the greatest risk factor for developing PD. Therefore, it is necessary to identify novel biomarkers associated with a...
Semi-supervised meta-learning elucidates understudied molecular interactions.
Communications biology
Sep 9, 2024
Many biological problems are understudied due to experimental limitations and human biases. Although deep learning is promising in accelerating scientific discovery, its power compromises when applied to problems with scarcely labeled data and data d...
Investigation of the potential molecular mechanisms of acupuncture in the treatment of long COVID: a bioinformatics approach.
Cellular and molecular biology (Noisy-le-Grand, France)
Sep 8, 2024
Long COVID is a poorly understood condition characterized by persistent symptoms following the acute phase of COVID-19, including fatigue, cognitive impairment, and joint pain. Acupuncture, a key component of traditional Chinese medicine treatment, h...
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