スキルを探す

Predict RBP binding from RNA sequence using deep learning models (RBPNet sequence-to-signal, RNAProt RNN, GraphProt2 GCN with structure, DeepCLIP, DeepRiPe multi-modal CNN) for variant-effect prediction, in silico binding-site discovery, model interpretation, and transfer learning from CLIP and RBNS datasets. Use when computational prediction of RBP binding from sequence is needed, evaluating variant effects on binding without further wet-lab experiments, comparing model performance, or training a custom model on ENCODE eCLIP 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。

Trains and applies base-resolution deep learning models on ChIP-seq / ChIP-nexus / CUT&RUN data. Uses BPNet (Avsec 2021 Nat Genet 53:354; soft motif syntax from ChIP-nexus), chromBPNet (Pampari A et al 2025 Nat Genet; bias-factorized base-resolution profiles), EnFormer (Avsec 2021 Nat Methods 18:1196; 196 kb input, ~100 kb effective receptive field), DeepSEA (Zhou 2015; multi-task CNN), and JASPAR 2026 deep-learning collection (1259 BPNet ChIP models). Performs in silico mutagenesis for variant-effect prediction, DeepLIFT/Grad attribution, and TF-MoDISco motif discovery from attribution scores. Use when predicting variant effects on TF binding, discovering soft motif syntax / cooperativity, integrating ChIP-seq with sequence-only predictions, or applying precomputed JASPAR Deep Learning models to new variants.

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。

Selects informative features for biomarker discovery using Boruta all-relevant selection, mRMR minimum redundancy, and LASSO regularization. Use when identifying biomarkers from high-dimensional omics 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。

Amplicon sequence variant (ASV) inference from 16S rRNA or ITS amplicon sequencing using DADA2. Covers quality filtering, error learning, denoising, and chimera removal. Use when processing demultiplexed amplicon FASTQ files to generate an ASV table for downstream analysis.

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。

Analyzes time-to-event data using Kaplan-Meier curves, log-rank tests, and Cox proportional hazards regression with lifelines. Builds survival models from clinical and omics features. Use when predicting patient survival or modeling time-to-event outcomes.

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。

Maps query single-cell data to reference atlases using scArches transfer learning with scVI and scANVI models. Transfers cell type labels without retraining on combined data. Use when annotating new single-cell datasets using pre-trained reference models.

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。

Biology research tools reference. Always available inside agent containers.

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。

Workflow for predictive modeling, biomarker discovery, survival modeling, and explainability over omics-derived 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。

通过 SandBase 搜索微博、追踪热搜、分析用户和话题趋势。适用于微博舆情监控、热点追踪、用户分析、品牌口碑研究等场景。

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 discussions, track communities, analyze posts, and discover trends on Reddit through SandBase. Use when asked for Reddit research, community analysis, trending topics, discussion monitoring, content discovery, or audience insight beyond customer-focused research.

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 WeChat Official Account articles, analyze account profiles, track article performance, and read comments. Covers article discovery, account profiling, engagement statistics, comment analysis, and content strategy research on China's dominant messaging ecosystem.

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 videos, analyze channel profiles, track live streams, and research content engagement on WeChat Channels (Video Accounts). Covers video search, channel profiling, live stream monitoring, comment analysis, and content collections.

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 any website for content changes, availability, performance, and security status. Combines page scraping, screenshot comparison, SSL monitoring, and security header checks for comprehensive website health and change detection.

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。

Get current weather conditions and forecasts for any location worldwide. Returns temperature, humidity, wind, precipitation, UV index, and multi-day forecasts. Useful for travel planning, event scheduling, and logistics coordination.

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 any topic in exhaustive depth by combining web search, academic papers, social discussions, and community conversations. Produces comprehensive briefings with evidence from every available source type, confidence scoring, and identified knowledge gaps.

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。

Track thought leaders and industry voices across LinkedIn, Twitter, and YouTube. Monitor publishing cadence, content themes, engagement patterns, and audience growth for competitive positioning and relationship-building 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。

Identify the technology stack powering any website — frameworks, CMS, analytics, hosting, CDN, payment processors, and marketing tools. Useful for competitive intelligence, sales prospecting, and technology landscape research.

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 conversations about any topic, brand, or keyword across Twitter, Reddit, Threads, Weibo, and community platforms simultaneously. Aggregates volume, sentiment, key voices, and emerging narratives across the global social 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。

Analyze sentiment in any text — reviews, social posts, feedback, or articles. Returns sentiment polarity (positive, negative, neutral), confidence score, and key phrases driving the sentiment. Useful for brand monitoring, customer feedback analysis, and content evaluation.

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。

Aggregate and analyze product and business reviews from Google Maps, Amazon, Akta, and Xiaohongshu. Cross-platform review intelligence including rating patterns, common themes, competitive comparison, and customer satisfaction trends.

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 and analyze product reviews from e-commerce and review sites. Aggregates ratings, identifies common themes in positive and negative feedback, and surfaces actionable product insights from customer voices across platforms.

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 products across Amazon, Google Shopping, and Xiaohongshu to understand pricing, reviews, market positioning, and consumer sentiment. Covers competitive product analysis, pricing benchmarks, feature comparison, and customer satisfaction signals.

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。

Track media coverage, press mentions, journalist activity, and industry narrative across news outlets, Twitter, and LinkedIn. Ideal for PR teams monitoring earned media, tracking campaign impact, and identifying journalist relationships.

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 potential partners by analyzing company profiles, product fit, market positioning, team background, and mutual connections. Combines firmographic data, content analysis, and social signals for partnership qualification and relationship mapping.

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。