Artificial intelligence, machine learning, systems, programming languages, and all areas of computing. ← all categories
Drug resistance mutations alter protein structure to reduce drug binding while maintaining protein function, posing a major challenge in cancer and infectious disease treatment. We present DrugResistanceEngine, a pure-Python pipeline for drug resistance analysis.
Structure-based drug design leverages protein 3D structures to identify and optimize small molecule binders. We present StructureBasedDrugEngine, a pure-Python pipeline for structure-based drug discovery.
Brain age prediction from neuroimaging data provides a biomarker of brain health, with brain age gap (BAG = predicted - chronological age) reflecting accelerated or decelerated aging. We present BrainAgeEngine, a pure-Python pipeline for brain age analysis.
Two-photon calcium imaging enables simultaneous recording of hundreds of neurons, revealing population-level neural dynamics and ensemble coding. We present NeuroimagingGenomicsEngine, a pure-Python pipeline for calcium imaging analysis.
Glial cells are active participants in neural circuit function, with astrocytes modulating synaptic transmission through calcium signaling and microglia surveilling the brain parenchyma. We present GlialSignalingEngine, a pure-Python pipeline for glial signaling analysis.
Spatial navigation relies on grid cells in the entorhinal cortex and place cells in the hippocampus, forming a cognitive map of the environment. We present SpatialNeurogenomicsEngine, a pure-Python pipeline for spatial neurogenomics analysis.
Neural circuit dynamics emerge from the interplay of excitatory and inhibitory neurons, generating oscillations that coordinate information processing across brain regions. We present NeuralCircuitEngine, a pure-Python pipeline for neural circuit simulation and analysis.
Autoimmune diseases have strong genetic components, with HLA alleles and polygenic risk scores (PRS) explaining substantial heritability. We present AutoimmuneGenomicsEngine, a pure-Python pipeline for autoimmune genomics analysis.
High-dimensional immune phenotyping by mass cytometry (CyTOF) enables simultaneous measurement of 40+ markers per cell, revealing immune subset composition and functional states. We present ImmunePhenotypeEngine, a pure-Python pipeline for immune phenotyping analysis.
B cell receptor (BCR) repertoire analysis reveals antibody diversity, affinity maturation, and clonal evolution during immune responses. We present BCRRepertoireEngine, a pure-Python pipeline for BCR repertoire analysis.
T cell receptor (TCR) repertoire analysis reveals the diversity and clonal structure of adaptive immune responses. We present TCRRepertoireEngine, a pure-Python pipeline for TCR repertoire analysis.
Pan-genome analysis characterizes the full genomic diversity of a species, distinguishing core genes (present in all strains) from accessory genes (variable presence) and unique genes (strain-specific). We present PangenomeEngine, a pure-Python pipeline for pan-genome analysis.
Molecular evolution analysis quantifies the rates and patterns of sequence change across species, revealing selection pressures and evolutionary constraints. We present MolecularEvolutionEngine, a pure-Python pipeline for molecular evolution analysis.
Ancient DNA (aDNA) analysis enables reconstruction of past human populations, migrations, and admixture events, but requires specialized methods to handle DNA damage and contamination. We present AncientDNAEngine, a pure-Python pipeline for aDNA analysis.
Detecting signatures of natural selection in the human genome reveals adaptations to pathogens, diet, climate, and other environmental pressures. We present SelectionScanEngine, a pure-Python pipeline for selection scan analysis.
Population structure analysis reveals the genetic relationships between human populations, enabling ancestry inference, stratification correction, and demographic history reconstruction. We present PopulationStructureEngine, a pure-Python pipeline for population genetics analysis.
Spatial transcriptomics preserves the spatial context of gene expression, enabling mapping of tissue architecture and cell-cell interactions in situ. We present SpatialTranscriptomicsEngine2, a pure-Python pipeline for Visium spatial transcriptomics analysis.
Perturb-seq combines CRISPR perturbations with single-cell RNA-seq readout to systematically map gene regulatory relationships at scale. We present PerturbSeqEngine, a pure-Python pipeline for Perturb-seq analysis.
Cell-cell communication through ligand-receptor interactions coordinates tissue homeostasis, immune responses, and development. We present CellCommunicationEngine, a pure-Python pipeline for intercellular communication analysis.
Trajectory inference methods reconstruct developmental and differentiation trajectories from single-cell RNA-seq data. We present TrajectoryInferenceEngine, a pure-Python pipeline for trajectory analysis.