Expert-level bioinformatics covering sequence analysis, structural bioinformatics, database searching, phylogenetic analysis, NGS data processing, single-cell analysis, and machine learning in biology.
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Pairwise alignment: Needleman-Wunsch (global), Smith-Waterman (local). Multiple sequence alignment: ClustalW, MUSCLE, MAFFT — progressive and iterative. Database search: BLAST — scoring matrix (BLOSUM62), E-value, bit score. Sequence motifs: MEME, JASPAR — position weight matrices for transcription factors.
Quality control: FastQC, trimming (Trimmomatic, fastp). Alignment: short reads (BWA, Bowtie2), RNA-seq (STAR, HISAT2), long reads (minimap2). Variant calling: GATK, FreeBayes, DeepVariant. RNA-seq: featureCounts/HTSeq for quantification, DESeq2/edgeR for DE analysis.
Protein structure: PDB format, secondary structure prediction (PSIPRED). Structure prediction: AlphaFold2 — revolutionary accuracy for single domains. Molecular docking: AutoDock, Glide — predicting protein-ligand binding. Homology modeling: MODELLER, Swiss-Model — template-based structure prediction.
scRNA-seq pipeline: Cell Ranger (10x), Seurat/Scanpy for analysis. Quality control: UMI counts, gene counts, mitochondrial fraction. Clustering: graph-based (Leiden, Louvain), UMAP/tSNE visualization. Trajectory analysis: RNA velocity, Monocle, PAGA.
BioPython: sequence parsing, BLAST interface, structure analysis. Pandas: tabular data — VCF files, expression matrices. Matplotlib/Seaborn: volcano plots, heatmaps, PCA plots. Scikit-learn: classification of sequences, feature extraction.
| Pitfall | Fix |
|---|---|
| Not checking alignment quality | Always review alignment stats and coverage |
| Ignoring multiple testing | Use FDR correction (Benjamini-Hochberg) |
| Wrong reference genome build | Confirm genome version matches annotation |
| Skipping normalization | Always normalize before comparing samples |
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概要と使いどころ
Expert-level abstract algebra knowledge. Use when working with groups, rings, fields, modules, Galois theory, representation theory, or algebraic structures. Also use when the user mentions 'group', 'ring', 'field', 'homomorphism', 'isomorphism', 'normal subgroup', 'quotient group', 'Sylow theorem', 'Galois theory', 'polynomial ring', 'ideal', 'module', 'vector space', or 'representation theory'.
日本語の概要は準備中です。原文の説明を表示しています。
Expert-level acoustics knowledge. Use when working with sound waves, acoustic propagation, resonance, standing waves, Doppler effect, room acoustics, ultrasound, noise control, musical acoustics, or architectural acoustics. Also use when the user mentions 'sound wave', 'decibel', 'frequency', 'resonance', 'standing wave', 'Doppler effect', 'acoustic impedance', 'reverberation', 'ultrasound', 'noise control', 'harmonics', or 'sound intensity'.
日本語の概要は準備中です。原文の説明を表示しています。
Expert-level aerodynamics covering subsonic and supersonic flow, lift and drag, airfoil theory, boundary layers, compressible flow, and CFD methods.
日本語の概要は準備中です。原文の説明を表示しています。
Expert-level air quality engineering covering pollutant sources, atmospheric dispersion, air quality standards, emission controls, and air quality modeling.
日本語の概要は準備中です。原文の説明を表示しています。
Expert-level aircraft structures covering structural design philosophy, wing and fuselage analysis, fatigue and damage tolerance, composite structures, and certification.
日本語の概要は準備中です。原文の説明を表示しています。
Expert-level algorithms and complexity theory covering sorting, searching, graph algorithms, dynamic programming, greedy algorithms, NP-completeness, and algorithm design paradigms.
日本語の概要は準備中です。原文の説明を表示しています。