AIMC Topic: Genomics

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Energy entropy vector: a novel approach for efficient microbial genomic sequence analysis and classification.

Briefings in bioinformatics
With the rapid development of genomic sequencing technologies, there is an increasing demand for efficient and accurate sequence analysis methods. However, existing methods face challenges in handling long, variable-length sequences and large-scale d...

Ensemble of Bayesian alphabets via constraint weight optimization strategy improves genomic prediction accuracy.

G3 (Bethesda, Md.)
This study proposes a weight optimization-based ensemble framework aimed at improving genomic prediction accuracy. It incorporates 8 Bayesian models-BayesA, BayesB, BayesC, BayesBpi, BayesCpi, BayesR, BayesL, and BayesRR in the ensemble framework, wh...

GPSai: A Clinically Validated AI Tool for Tissue of Origin Prediction during Routine Tumor Profiling.

Cancer research communications
UNLABELLED: A subset of cancers present with unclear or potentially incorrect primary histopathologic diagnoses, including cancers of unknown primary (CUP). We aimed to develop and validate an artificial intelligence (AI) tool, Genomic Probability Sc...

Generating realistic artificial human genomes using adversarial autoencoders.

NAR genomics and bioinformatics
A publicly available human genome is both valuable to researchers and a risk for its donor. Many actors could exploit it to extract information about the donor's health or that of their relatives. Recent efforts have employed artificial intelligence ...

Optimizing genomic prediction with transfer learning under a ridge regression framework.

The plant genome
Genomic selection (GS) is a predictive plant and animal methodology that allows the selection of plants and animals based on predictions without the need to measure the phenotype. However, its practical application requires challenging prediction acc...

A comprehensive targeted panel of 295 genes: Unveiling key disease initiating and transformative biomarkers in multiple myeloma.

Computers in biology and medicine
BACKGROUND: Multiple myeloma (MM) is a hematological malignancy that progresses from a benign precursor stage known as Monoclonal Gammopathy of Undetermined Significance (MGUS). Distinguishing MM from MGUS at the molecular level by identifying key bi...

External Validation of a CT-Based Radiogenomics Model for the Detection of EGFR Mutation in NSCLC and the Impact of Prevalence in Model Building by Using Synthetic Minority Over Sampling (SMOTE): Lessons Learned.

Academic radiology
RATIONALE AND OBJECTIVES: Radiogenomics holds promise in identifying molecular alterations in nonsmall cell lung cancer (NSCLC) using imaging features. Previously, we developed a radiogenomics model to predict epidermal growth factor receptor (EGFR) ...

Methodological opportunities in genomic data analysis to advance health equity.

Nature reviews. Genetics
The causes and consequences of inequities in genomic research and medicine are complex and widespread. However, it is widely acknowledged that underrepresentation of diverse populations in human genetics research risks exacerbating existing health di...

Novel natural vector with asymmetric covariance for classifying biological sequences.

Gene
The genome sequences of organisms form a large and complex landscape, presenting a significant challenge in bioinformatics: how to utilize mathematical tools to describe and analyze this space effectively. The ability to compare relationships between...

Genomic and machine learning approaches to predict antimicrobial resistance in .

Microbiology spectrum
UNLABELLED: is a multidrug-resistant pathogen, which poses a major challenge to clinical management due to its increasing resistance to common antibiotics, such as levofloxacin (LEV) and trimethoprim-sulfamethoxazole (SXT), and poor clinical respons...