“pdb”的搜索结果

Automate Abuselpdb tasks via Rube MCP (Composio). Always search tools first for current schemas.

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Analyzes indicators of compromise (IOCs) including IP addresses, domains, file hashes, URLs, and email artifacts to determine maliciousness confidence, campaign attribution, and blocking priority. Use when triaging IOCs from phishing emails, security alerts, or external threat feeds; enriching raw IOCs with multi-source intelligence; or making block/monitor/whitelist decisions. Activates for requests involving VirusTotal, AbuseIPDB, MalwareBazaar, MISP, or IOC enrichment pipelines.

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Automate Abuselpdb tasks via Rube MCP (Composio). Always search tools first for current schemas.

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Access AlphaFold DB's 200M+ predicted structures by UniProt ID. Download PDB/mmCIF, analyze pLDDT/PAE, bulk-fetch proteomes via Google Cloud. For experimental structures use PDB; for prediction use ColabFold or ESMFold.

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Analyzes indicators of compromise (IOCs) including IP addresses, domains, file hashes, URLs, and email artifacts to determine maliciousness confidence, campaign attribution, and blocking priority. Use when triaging IOCs from phishing emails, security alerts, or external threat feeds; enriching raw IOCs with multi-source intelligence; or making block/monitor/whitelist decisions. Activates for requests involving VirusTotal, AbuseIPDB, MalwareBazaar, MISP, or IOC enrichment pipelines.

中文简介正在准备中。当前显示原文说明。

Automate Abuselpdb tasks via Rube MCP (Composio). Always search tools first for current schemas.

中文简介正在准备中。当前显示原文说明。

Automate Abuselpdb tasks via Rube MCP (Composio). Always search tools first for current schemas.

中文简介正在准备中。当前显示原文说明。

Debug Python: pdb REPL + debugpy remote (DAP).

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Analyzes indicators of compromise (IOCs) including IP addresses, domains, file hashes, URLs, and email artifacts to determine maliciousness confidence, campaign attribution, and blocking priority. Use when triaging IOCs from phishing emails, security alerts, or external threat feeds; enriching raw IOCs with multi-source intelligence; or making block/monitor/whitelist decisions. Activates for requests involving VirusTotal, AbuseIPDB, MalwareBazaar, MISP, or IOC enrichment pipelines.

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Look up genes, sequences, protein structures, expression patterns, and disease associations across more than 20 bioinformatics resources using command-line tools or Python. Useful for interactive exploration, with results that can be saved for further analysis.

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• Looking up gene details and sequences
• Exploring protein structures and residue annotations
• Comparing tissue expression and disease associations

Build a central platform for collecting, analyzing, and sharing cyber threat information. Connect MISP, OpenCTI, TheHive, and Cortex to import feeds, add context to suspicious indicators, manage cases, and track platform activity.

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• Build a central threat intelligence platform
• Automate threat feed ingestion
• Add context to suspicious IP addresses and domains

Analyze suspicious email headers to trace delivery routes and assess sender spoofing. Review SPF, DKIM, and DMARC sender authentication results, compare sender and reply addresses, and examine links and attachment hashes for phishing indicators.

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• Triaging a suspicious email reported by a user
• Checking whether a sender domain was spoofed
• Tracing the delivery route of a phishing email

Plans, executes, and validates Google Kubernetes Engine upgrades for Standard and Autopilot clusters. Creates environment-specific upgrade plans, checklists, and command-based runbooks, with guidance on maintenance timing, node upgrade strategies, workload readiness, and stalled upgrades.

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• Planning a GKE version upgrade
• Choosing release channels and maintenance schedules
• Preparing node pool upgrades for databases or GPU workloads

Investigate errors, crashes, and unexpected behavior by reproducing failures, tracing execution, and comparing logs. Tests one explanation at a time, then provides a verified fix, supporting evidence, and tests or safeguards to prevent recurrence.

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• Investigate error messages and execution traces
• Find the cause of an application crash
• Compare logs to locate a failure

Screen supplied proteins, peptides, antibodies, or nanobodies against a target with Boltz. Prepares inputs, obtains a cost estimate for approval, downloads results, and ranks candidates by binding confidence, a score for predicted binding reliability.

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• Rank existing protein binders against a target
• Compare antibody or nanobody candidates
• Screen candidates using target sequences alone

Build PyTorch machine learning workflows for molecules, proteins, and biomedical relationships. Get guidance on datasets, model selection, training, and evaluation for property prediction, protein modeling, molecule generation, and planning synthesis routes from target molecules.

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• Predicting molecular solubility and toxicity
• Predicting protein function from sequences or structures
• Exploring new drug uses through biomedical relationships

Search UniProt for proteins by name, gene, or organism and retrieve sequences and functional annotations. Supports FASTA, a text format for sequences, identifier conversion between databases, batch retrieval, and downloads of large result sets through its REST API.

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• Search proteins by gene name and organism
• Retrieve protein sequences in FASTA format
• Convert identifiers between UniProt and other databases

Look up biological evidence about genes, variants, diseases, pathways, and proteins across databases. Map identifiers between sources and organize findings into comparison tables that preserve source names, query terms, access dates, and access limitations.

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• Map gene identifiers across databases
• Gather evidence on variant clinical significance
• Compare target–disease association evidence

Predict protein structures by connecting MSA-Search with OpenFold3. It finds related sequences, aligns them to provide evolutionary context, and saves predicted structures with confidence scores. It also supports comparing predictions with and without that context.

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• Predict protein structures using related sequences
• Save alignments, structures, and confidence scores
• Compare predictions with and without alignment context

Generate and screen small-molecule drug candidates with three NVIDIA BioNeMo NIM services. Use GenMol to create molecules, DiffDock to predict how they fit a target protein, and Boltz2 to estimate binding strength and rank candidates.

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• Generating and screening candidates without a starting scaffold
• Exploring analogs of a known molecular scaffold
• Screening a candidate library against a protein target

Use when you want to search for or download experimentally-determined 3D structures for biomolecules (proteins, nucleic acids, bound ligands). Supports searching by sequence similarity, structure similarity, chemical and other attributes. Also use to get metadata about biomolecular structure experiments.

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Reads, writes, and converts molecular file formats (SMILES, SDF, MOL2, PDB) using RDKit and Open Babel. Handles structure parsing, canonicalization, and full standardization pipeline including sanitization, normalization, and tautomer canonicalization. Use when loading chemical libraries, converting formats, or preparing molecules for analysis.

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Access AlphaFold's 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.

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Review generated or changed WordPress code — plugins, themes, and blocks — before it ships. Best used reactively after an agent writes, edits, or reviews code touching WordPress APIs: add_action/add_filter, shortcodes, meta boxes, AJAX handlers, REST routes, WP_Query or $wpdb, widgets, or WP-CLI commands. Use on 'review this plugin', 'is this safe to ship', 'make this translatable', 'speed up this query', or after tasks like 'write a plugin' or 'add an endpoint/shortcode/meta box'. Enforces escaping and sanitization, nonces plus capability checks, prepared database queries, core-API-first development, translation-ready strings, and query/caching discipline. DO NOT USE for WooCommerce-specific order, product, or checkout logic (use woo-guard), non-WordPress PHP, generic code quality review (use clean-code-guard), test code review (use test-guard), server or hosting configuration, or conceptual WordPress questions.

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