職業

Microbiologists

355 スキル

AIに聞く

355 スキル

featureCounts — RNA-seq Read Counting

Counts aligned RNA-seq reads overlapping gene features in a GTF annotation. Takes sorted BAM files from STAR alignment and a GTF file; outputs a tab-delimited count matrix per gene across all samples. Handles strandedness (0=unstranded, 1=stranded, 2=reverse-stranded), paired-end, and multi-sample batch counting in a single command. Use Salmon instead for alignment-free quantification; use featureCounts when STAR BAMs already exist and a gene-level count matrix is needed.

jaechang-hits119

メディア

Pyimagej Fiji Bridge

Python bridge to ImageJ2/Fiji enabling macro execution, plugin calls (Bio-Formats, TrackMate, Analyze Particles), bidirectional NumPy↔ImagePlus/ImgLib2 data exchange, and ImageJ Ops from Python. Use for automating Fiji-specific workflows headlessly from Python scripts. Use scikit-image instead for pure Python pipelines that do not require Fiji plugins; use napari for interactive visualization.

jaechang-hits119

科学計算

Pathml

PathML is an open-source toolkit for computational pathology. Use it to process whole-slide images (WSIs): load slides, extract tiles, apply stain normalization and nuclear segmentation preprocessing, extract features, and train machine learning models. Supports H&E and multiplex imaging. Ideal for building end-to-end digital pathology pipelines from raw WSI files to quantitative outputs.

jaechang-hits119

天文学・物理学

Flowio Flow Cytometry

Parse and create FCS (Flow Cytometry Standard) files v2.0-3.1. Read event data as NumPy arrays, extract channel metadata, handle multi-dataset files, export to CSV/FCS. For advanced gating and compensation use FlowKit.

jaechang-hits119

デバッグ

SimpleITK Image Registration and Analysis

Register, segment, filter, and resample 3D medical images (MRI, CT, microscopy) using SimpleITK's Python API with support for DICOM, NIfTI, and multi-modal image analysis. Provides rigid/affine/deformable registration, threshold and region-growing segmentation, Gaussian and morphological filtering, label statistics, and format conversion. Use when aligning volumetric images across timepoints or modalities, automating segmentation of fluorescence microscopy, or converting DICOM series to NIfTI for analysis pipelines.

jaechang-hits119

科学計算

Cellpose — Deep Learning Cell Segmentation

Deep learning cell and nucleus segmentation from fluorescence and brightfield microscopy images. Uses pre-trained models (cyto3, nuclei, tissuenet) and a generalist flow-based algorithm that segments cells without requiring retraining on new image types. Outputs label masks for downstream morphology measurement and tracking. Use scikit-image watershed for rule-based segmentation; use Cellpose when deep learning generalization across staining conditions is needed.

jaechang-hits119

Microbiologists

featureCounts — RNA-seq Read Counting

Pyimagej Fiji Bridge

Pathml

Flowio Flow Cytometry

SimpleITK Image Registration and Analysis

Cellpose — Deep Learning Cell Segmentation

Microbiologists

featureCounts — RNA-seq Read Counting

Pyimagej Fiji Bridge

Pathml

Flowio Flow Cytometry

SimpleITK Image Registration and Analysis

Cellpose — Deep Learning Cell Segmentation

pLannotate Plasmid Annotation

Omero Integration

Pubchem Compound Search

torchdrug

DrugBank Database — Local XML Access

SpikeInterface — Unified Extracellular Electrophysiology Framework

Researchers Security

Checking Chembl For Structured Sar Data

Pyopenms

Matchms

Flowio

Cbioportal Database

Tooluniverse Antibody Engineering

Flowio

Clinvar Database

Opentargets Database

Benchling Integration

Pubmed Summariser

Bio Clinical Databases Gnomad Frequencies

Bio Proteomics Spectral Libraries

Microbiome Cancer Agent

Bio Variant Calling Clinical Interpretation

Bio Flow Cytometry Clustering Phenotyping

Chromosomal Instability Agent