AIMC Topic: Software

Clear Filters Showing 11 to 20 of 3675 articles

MLDeCNV: A machine learning approach for predicting copy number variation types in plant genomes.

Computers in biology and medicine
Copy number variations (CNVs) play a crucial role in shaping genetic diversity and influencing various plant traits. However, existing methods for CNV characterization often face challenges due to the complexity and repetitive nature of plant genomes...

Image Generation of Common Dermatological Diagnoses by Artificial Intelligence: Evaluation Study of the Potential for Education and Training Purposes.

JMIR dermatology
BACKGROUND: The integration of artificial intelligence (AI) into dermatology holds promise for education and diagnostic purposes, particularly through image generation, which has not been well studied.

Diagnostic performance of four AI tools in pharmacology MCQs: Accuracy, sensitivity, and specificity.

PloS one
BACKGROUND: The rapid rise of AI in medical and pharmaceutical education has engendered much interest; however, a knowledge gap still exists in the evaluation of performances of these tools in critical academic contexts.

Graph-based deep reinforcement learning for haplotype assembly with Ralphi.

Genome research
Haplotype assembly is the problem of reconstructing the combination of alleles on the maternally and paternally inherited chromosome copies. Individual haplotypes are essential to our understanding of how combinations of different variants impact phe...

The Omics Molecule Extractor: A Web Application for the Selection of Potential Biomarker Panels.

Journal of proteome research
Selecting molecular panels that are applicable to classify the health state of patients is a common task in omics data analysis. Existing software for molecule selection lacks features to select molecule panels from large data sets, requires programm...

A scalable equivariant graph network framework for precise protein function prediction.

Genome biology
BACKGROUND: Protein function research helps in understanding the complex biological processes that occur within cells. However, the intricate nature of protein structures and functions, along with the rapid growth of protein sequence data, presents a...

SpecQuality: A Tool for Reliable Spectral Quality Assessment in Proteomics and Proteogenomics.

Journal of the American Society for Mass Spectrometry
Proteogenomics integrates genomics and mass spectrometry (MS) data to understand complex biological systems, disease mechanisms, and potential biomarkers. However, the high volume and noise in MS data present computational and interpretational challe...

SPACEc: a streamlined, interactive Python workflow for multiplexed image processing and analysis.

Nature communications
Multiplexed imaging has transformed our ability to study tissue organization by capturing thousands of cells and molecules in their native context. However, these datasets are enormous, often comprising tens of gigabytes per image, and require comple...

eRMSF: A Python Package for Ensemble-Based RMSF Analysis of Biomolecular Systems.

Journal of chemical information and modeling
Understanding molecular flexibility and dynamics across different structural ensembles is essential for interpreting the behavior of complex biological systems. Here, we introduce eRMSF, a fast and user-friendly Python package built with MDAKit from ...

Talk2Biomodels: AI agent-based open-source LLM initiative for kinetic biological models.

BMC bioinformatics
BACKGROUND: Quantitative kinetic models of biological regulatory processes play an important role in understanding disease mechanisms. However, their simulation and analysis require specialized domain expertise.