682 件 ・ 関連度順
概要と使いどころ
Use when asked 帮我写教案, 写一份新课标教案, 教学设计, 单元教学设计, 大单元教案, or a lesson plan in the format Chinese schools expect. Produces a complete 教案 in Chinese with 教材分析, 学情分析, 教学目标 tied to the subject's 核心素养, 教学重难点, 教学方法, a timed 教学过程 with teacher and student activity, 板书设计, layered 作业设计 within the 双减 time limits, and 教学反思 prompts, with curriculum references marked to confirm against the current 课程标准.
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。
Write clear at-home care instructions for a pet owner after a veterinary visit, procedure, or hospitalization. Use when asked to write discharge instructions, go-home notes, post-op care, or medication instructions for a pet owner. Produces plain-language home-care instructions: medications (what/how much/when/how), activity restrictions, what to watch for, warning signs that mean call-now, the recheck plan, and emergency contacts — written so a worried owner can actually follow them.
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。
Summarize AI conversation histories for a specified date or period. Use for daily work recaps and cross-tool activity summaries.
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。
Monitor brand mentions, competitor activity, and industry conversations across social media and the web
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。
Scrape recent posts from LinkedIn profiles using Apify. Use when you need to monitor what specific people are posting on LinkedIn, track founder/exec activity, or gather LinkedIn content for competitive intelligence.
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。
Extract leads from competitor product activity — Product Hunt commenters/upvoters, HN posts about competitors, case studies, testimonials, tech press, and switching signals. Detects people actively switching from competitors as highest-priority leads.
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。
Research LinkedIn profiles and write personalized messages for any LinkedIn message type — connection requests, InMails, DMs, message requests, post comments, and comment replies. Takes LinkedIn URLs as input, researches each person (profile data + recent posts via Apify), and generates messages tailored to each lead's background, interests, and recent activity. Exports tool-ready CSVs for Dripify, Expandi, Botdog, PhantomBuster, or generic format. No LinkedIn cookies or login required.
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。
Build a prospect list of companies with decision makers, verified contact info, and hiring/intent signals. Use when asked to find leads by industry, build an account list with specific titles, prospect companies that are actively hiring, or create a targeted outreach list filtered by company size, location, and hiring activity.
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。
Search for job postings across LinkedIn and Indeed. Use when users want to find open roles, monitor hiring signals, identify companies hiring for specific positions, or research competitor hiring activity. Returns job title, company, location, salary, description, seniority level, and direct apply URLs. No login or cookies required.
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。
Comprehensive GTM analysis of any target company. Researches what a company is currently doing across all go-to-market dimensions — content/blog, founder LinkedIn activity, SEO/traffic, hiring signals, social/community presence, customer acquisition channels, podcast appearances, review sites, competitive positioning, and partnerships. Produces a structured report identifying what's working, what's missing, and where white space exists for new strategies. Use before designing GTM strategies for a client or prospect.
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。
Designs cytosine (CBE, C-to-T) and adenine (ABE, A-to-G) base-editor guides by positioning the target base at the activity-peak of the editing window (protospacer positions ~5-7, PAM-distal numbering), minimizing bystander edits for product purity, reading dinucleotide context (APOBEC1 TC favored / GC disfavored), and selecting the editor variant (BE4max, ABEmax, ABE8e, YE1/SECURE, TadCBE, CGBE, SpG/SpRY-BE). Covers knockout by premature stop (CRISPR-STOP/iSTOP) and splice-site disruption, the three off-target classes (Cas-dependent, Cas-independent DNA, RNA), outcome prediction (BE-Hive/DeepBE), and the base-vs-prime-vs-HDR decision. Use when installing a transition mutation without a double-strand break, knocking out a gene without indels, or choosing CBE vs ABE. Generic guide scoring, prime editing, and HDR donors are separate skills.
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。
Detects A/B chromatin compartments from balanced Hi-C contact matrices via eigenvector decomposition of the distance-normalized, Pearson-correlated cis matrix with cooltools (eigs_cis), then orients (phases) the compartment eigenvector against a GC or gene-density track so the active (A) sign is not arbitrary. Covers the eigenvector-is-a-choice problem (per-arm view_df to remove the centromere gradient; picking the eigenvector by max correlation with activity, not by eigenvalue), GC phasing with bioframe.frac_gc, resolution choice (100kb-1Mb), saddle plots and saddle_strength for compartmentalization strength, the cohesin-loss-strengthens-compartments result, subcompartments (SNIPER/Calder/dcHiC), and cross-condition compartment switching. Use when calling A/B compartments, computing E1/eigenvectors, phasing the eigenvector, building saddle plots, choosing a compartment resolution, quantifying compartment strength, or comparing compartmentalization across conditions.
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。
Nominates and assesses CRISPR off-target sites genome-wide. Enumerates candidate sites by mismatch and bulge tolerance with Cas-OFFinder/CRISPRitz, ranks them with the published CFD score (SpCas9-only, relative ranker) or MIT/CRISTA/energy models, runs variant-aware screening against gnomAD/individual genomes (CRISPRme), and frames the empirical genome-wide discovery assays (GUIDE-seq, CIRCLE-seq, CHANGE-seq, DISCOVER-seq, Digenome-seq) and high-fidelity nuclease choice (HiFi Cas9, Sniper-Cas9, eSpCas9, SpCas9-HF1). Use when assessing guide RNA specificity, choosing among candidate guides, screening a therapeutic guide against population variation, or planning empirical off-target validation. Distinguishes predicted vs detected vs validated. On-target activity scoring and deaminase (Cas-independent) base/prime-editor off-targets are separate skills.
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。
Designs and ranks guide RNAs (sgRNAs) for CRISPR-Cas9/Cas12a gene knockout by scanning a target for PAM sites (NGG SpCas9, NNGRRT SaCas9, TTTV Cas12a, NG SpCas9-NG, near-PAMless SpRY), enumerating candidate spacers, applying hard filters (Pol-III TTTT terminator, 5' G, GC), ranking on-target activity with the context-appropriate model (Rule Set 2/Azimuth for U6/lentiviral, CRISPRscan for T7/embryo, DeepHF for high-fidelity variants, DeepCpf1 for Cas12a), and predicting the indel/frameshift outcome (Bae out-of-frame score, inDelphi, FORECasT, Lindel). Use when selecting sgRNAs to knock out a gene, choosing a nuclease/PAM for a constrained locus, picking which exon to target, or shortlisting guides before an off-target check. Off-target specificity, base/prime editing, and HDR donors are separate skills.
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。
Queries PharmGKB / CPIC / DPWG for drug-gene interactions; calls CYP2D6/CYP2C9/CYP2C19/DPYD/TPMT/NUDT15/UGT1A1/SLCO1B1 star alleles and phenotype with PharmCAT, Cyrius (CYP2D6 structural variants), Aldy, Stargazer; applies Caudle 2020 activity-score translation. Use when implementing pharmacogenomic-guided prescribing, applying CPIC vs DPWG guidance, screening HLA risk alleles for ICI / antiepileptics / abacavir, or interpreting compound TPMT+NUDT15 thiopurine risk.
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。
Designs novel molecules using REINVENT 4 (de novo, scaffold decoration, linker design, R-group, molecular optimization), MolMIM, Diffusion-based generators (DiGress, DiffSMol), and JT-VAE with explicit handling of multi-parameter optimization (MPO), goal-directed scoring functions, transfer/reinforcement/curriculum learning, synthetic accessibility scoring, and chemical space exploration vs exploitation. Use when designing new chemical matter against a target, decorating a scaffold, linking fragments, or optimizing a hit for multiple ADMET / activity properties simultaneously.
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。
Enumerates virtual chemical libraries via reaction SMARTS transformations using RDKit and reaction templates, with explicit handling of atom mapping, RDChiral template extraction, product validation, RECAP/BRICS fragmentation, R-group decomposition, matched molecular pair analysis (MMPA), and Free-Wilson analysis. Use when generating combinatorial libraries from building blocks, enumerating analog series, deriving structure-activity rules, or extracting transformations from reaction data.
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。
Detect transcription factor binding footprints in ATAC-seq using TOBIAS, HINT-ATAC, Wellington, or scprinter. Use when identifying bound TF sites within accessible regions, correcting Tn5 insertion bias before footprinting, choosing between cleavage-based and aggregate-based footprinters, or comparing differential TF activity between conditions.
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。
Build shared real-time experiences using GroupActivities and SharePlay. Use when implementing shared media playback, collaborative app features, synchronized game state, or any FaceTime, Messages, AirDrop, or nearby visionOS group activity on iOS, macOS, tvOS, or visionOS.
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。
Implement AlarmKit alarms and countdown timers for iOS and iPadOS with Lock Screen, Dynamic Island, StandBy, and paired Apple Watch system UI. Covers AlarmManager scheduling, AlarmAttributes and AlarmPresentation, system Stop and AlarmButton secondary actions, authorization, state observation, countdown widget-extension handoff, and Live Activity integration. Use when building wake-up alarms, countdown timers, or alarm-style alerts that need Apple's system alarm experience.
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。
Build iOS App Clips with invocation URLs, App Clip Codes, NFC, QR codes, Safari banners, Maps, Messages, target setup, App Store Connect experiences, size/capability constraints, NSUserActivity routing, SKOverlay promotion, App Group/keychain handoff, ephemeral notifications, location confirmation, and full-app migration. Use when creating App Clips or wiring App Clip invocation, experience configuration, or full-app handoff.
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。
Access Core Motion accelerometer, gyroscope, magnetometer, device-motion, pedometer, activity-recognition, altitude, headphone motion, batched high-frequency workout motion, and water-submersion/depth data. Use when reading device sensors, counting steps, detecting walking/running/driving/cycling, tracking altitude, building motion interactions, handling AirPods head tracking, or implementing watchOS dive/depth features.
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。
Smart triggered RF capture on NI USRP radios with Wireless Testbench — record only when a signal of interest appears, not continuously (triggered spectrum sensing). Use energy detection to capture when signal power rises above the noise floor, or preamble detection to cross-correlate against a known sequence (WLAN L-LTF, 5G NR PSS/SSS, LTE PSS, Zadoff-Chu, custom protocols) and capture only when that protocol's preamble is detected. Use when implementing triggered (wake-on-signal) capture or spectrum sensing, capturing protocol-based signals via cross-correlation, calibrating detection thresholds (plotDetectionSignals / plotThreshold), scanning frequency bands for activity, or building transmit-then-detect workflows.
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。
Create and customize MATLAB charts and plots. Plot types (line, scatter, bar, histogram, heatmap, surface), axes configuration, annotations, data tips, interactive plots, animation, multiple axes with tiledlayout, colororder, and performance optimization. Works for standalone figures, Live Scripts, and uifigure apps. Use when plotting data, customizing axes, adding annotations or interactivity, animating charts, or arranging multiple axes. Triggers: plot, chart, graph, axes, uiaxes, annotation, data tips, animation, tiledlayout, colororder, heatmap, scatter, figure, visualization, export.
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。