'binding' 검색 결과

Performs alchemical free-energy calculations including relative binding free energy (RBFE / FEP+) and absolute binding free energy (ABFE) via OpenFE, FEP+, GROMACS, AMBER pmemd, and OpenMM with explicit lambda window scheduling, soft-core potentials, REST2 enhanced sampling, MBAR/BAR analysis, and cycle closure validation. Compares ML alternatives (Boltz-2 affinity, DeepDock). Use when ranking analogs by binding affinity beyond docking accuracy, performing prospective lead optimization, or validating SAR predictions.

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Identify tumor neoantigens from somatic variants with pVACtools (pVACseq/pVACfuse/pVACbind/pVACvector/pVACview) for personalized cancer vaccines and checkpoint biomarkers. Encodes the field's hard truth that binding prediction is the easy, near-solved part and single-digit-percent PPV lives downstream — so it centers clonality/CCF, HLA LOH (the silent invalidator), expression, proximal-variant phasing, agretopicity/foreignness quality, and the predicted->presented->immunogenic validation tiers. Use when nominating vaccine targets, ranking neoantigens, or building a tumor-to-candidate pipeline. Binding details in mhc-binding-prediction; ranking in immunogenicity-scoring.

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Predict peptide-MHC class II (HLA-DR/DQ/DP) binding and presentation for CD4 T-cell epitopes with NetMHCIIpan-4.3 and MixMHC2pred-2.0. Covers why class II is far less reliable than class I (open binding groove, 9-mer register ambiguity, sparse noisy training data, DR>DP>DQ accuracy asymmetry), the DQ/DP heterodimer alpha/beta pairing trap, and the looser 1%/5% %Rank thresholds. Use when predicting CD4 epitopes for vaccine help, mapping class II neoantigens, or scoring long peptides against DR/DQ/DP. For CD8/class I see mhc-binding-prediction.

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Infer or annotate TCR antigen specificity by unsupervised clustering (TCRdist/tcrdist3, GLIPH2, clusTCR, GIANA) and database lookup (VDJdb, IEDB, McPAS-TCR), and rank candidates with supervised predictors (ERGO-II, NetTCR-2.x, pMTnet) under explicit caveats. Encodes the central truth that general TCR-epitope prediction for UNSEEN epitopes essentially does not work (collapses to near-random; IMMREP22, Grazioli 2022) because labeled data is dominated by a few immunodominant epitopes and there is no true negative set — so clustering for discovery is the honest task and de-novo binding needs wet-lab validation. Use when annotating TCR specificity or grouping a repertoire. Epitope/MHC context lives in mhc-binding-prediction.

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Performs alchemical free-energy calculations including relative binding free energy (RBFE / FEP+) and absolute binding free energy (ABFE) via OpenFE, FEP+, GROMACS, AMBER pmemd, and OpenMM with explicit lambda window scheduling, soft-core potentials, REST2 enhanced sampling, MBAR/BAR analysis, and cycle closure validation. Compares ML alternatives (Boltz-2 affinity, DeepDock). Use when ranking analogs by binding affinity beyond docking accuracy, performing prospective lead optimization, or validating SAR predictions.

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Detects allele-specific transcription factor or histone modification binding from heterozygous-variant ChIP-seq using WASP (reference-bias filter; mandatory upstream), RASQUAL (joint QTL + bias-corrected testing), BaalChIP (Bayesian beta-binomial with copy-number-aware overdispersion), and AlleleSeq (personalized diploid genome). Handles imprinted-locus awareness, X-inactivation artifacts, cancer copy-number imbalance, and integration with downstream caQTL / bQTL mapping. Use when identifying variants with allelic effects on TF binding, fine-mapping causal regulatory variants, validating deep-learning variant predictions, or characterizing cis-acting regulatory effects.

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Harden LDAP directory services against common attacks including credential harvesting, LDAP injection, anonymous binding, and channel binding bypass. Covers LDAPS enforcement, channel binding, LDAP si

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Investigate Kubernetes permissions and cluster behavior in CTF sandboxes. Trace role-based access control, service accounts, and automated controllers to explain workload changes, secret exposure, and differences between configuration files and live objects.

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• Checking service account API permissions
• Tracing secret exposure through workload changes
• Comparing YAML manifests with live cluster objects

Connect Table v9 state to Alpine bindings and manage pagination from application code. Explains reactive reads, getter and callback setup, shared state atoms, and why some captured values fail to follow later updates.

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• Control pagination from Alpine state
• Display current table state in Alpine bindings
• Investigate stale values after state replacement

Connect Slack to Kortix and handle team conversations through the Slack CLI. Show live progress, send formatted replies, share files, and search messages, with thread binding that routes follow-up replies back to the same agent session.

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• Connect a Slack workspace to Kortix
• Show task progress and results in a Slack thread
• Share generated files in Slack

Write and review Cloudflare Workers code using current official guidance. Check configuration, asynchronous tasks, large response handling, secrets, and service connections, with findings supported by documentation, code locations, or validation results.

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• Writing a new Cloudflare Worker
• Reviewing Workers code before production use
• Checking wrangler.jsonc and service bindings

Screen an existing compound library against a protein target with Boltz. Rank candidates by binding confidence or lead optimization score, download predicted structures, and review solubility, permeability, and lipophilicity results alongside the ranked hits.

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• Screening an existing compound library against a protein
• Finding candidates with high binding confidence
• Comparing candidates for lead optimization

Build Vue 3 components with TypeScript and Composition API, a way to organize component logic. Define inputs, events, and two-way bindings, manage reactive data, and use built-in components for transitions and state preservation.

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• Build Vue components with TypeScript
• Define component inputs, events, and two-way bindings
• Update displays and react to data changes

Build scrollable lists and grids in .NET MAUI using CollectionView. The guidance covers item layouts, selection, grouping, refresh gestures, incremental loading, swipe actions, and empty states, with examples and checks for common implementation mistakes.

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• Building scrollable lists or grids in .NET MAUI
• Adding item selection and grouped displays
• Implementing pull-to-refresh and incremental loading

Build page navigation in .NET MAUI apps using Shell. Configure tabs and slide-out menus, register page routes, pass data between pages, and add confirmation dialogs before users leave a page.

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• Setting up tabs and slide-out menus
• Passing data to a detail page
• Confirming before leaving unsaved changes

Test whether CAPTCHA protections actually block form actions on the server. The skill checks missing or empty fields, reused tokens, tokens accepted for other actions, and inconsistent enforcement, then confirms bypasses through completed actions such as registration or login.

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• Checking CAPTCHA enforcement on login forms
• Testing registration and password-reset endpoints
• Verifying token reuse and action binding

Build interactive React cards and forms from JSON commands sent by an AI agent. Using @ant-design/x-card and A2UI, a protocol for describing interfaces, this skill covers data binding, user actions, custom components, and progressive rendering.

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• Display interactive cards inside AI chat responses
• Build forms driven by agent commands
• Render an interface progressively as commands arrive

Create or refactor SwiftUI screens with practical patterns for tabs, navigation, sheets, layouts, and state ownership. It also guides asynchronous loading, previews, accessibility labels, and build checks while respecting the project's conventions and supported OS versions.

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• Creating a new tabbed SwiftUI app structure
• Splitting large screens into focused components
• Organizing state ownership and data flow

NOTE: molecule and target inputs and your NGC_API_KEY are transmitted to external NVIDIA-hosted API endpoints on every call. Use local NIM containers for confidential or proprietary data. Run a complete computational drug discovery pipeline using NVIDIA BioNeMo NIMs: generate drug-like molecules with GenMol, dock them to a protein target with DiffDock, then predict binding affinity with Boltz2. Use this skill whenever the user wants to generate and screen small molecule drug candidates, perform hit discovery, optimize leads against a protein target, or do virtual screening combining molecule generation, docking, and affinity prediction. Triggers on: drug discovery pipeline, hit discovery, lead optimization, virtual screening, molecule generation, molecular docking, binding affinity, GenMol, DiffDock, Boltz2, SMILES, SAFE notation, NIM microservice. This is a multi-step pipeline composing three BioNeMo NIMs.

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Queries the UniBind database for experimentally validated transcription factor (TF) binding sites. Use when retrieving direct TF-DNA interaction datasets, downloading binding site coordinates (BED/FASTA) for local analysis, or listing available datasets by species, cell line, or TF name. Don't use to query specific intervals, locations, genes, motif models or expression data.

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Detect transcription factor binding sites through footprinting analysis in ATAC-seq data using TOBIAS. Use when identifying TF occupancy patterns within accessible regions, as TF binding protects DNA from Tn5 cutting.

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DNS rebinding attack playbook. Use when testing applications that trust DNS resolution for origin checks, interact with internal services from browser context, or when SSRF is not possible server-side but the target has client-side fetch/XHR to attacker-controlled domains.

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Set up player input in Unreal Engine 5 with Enhanced Input: Input Actions, Input Mapping Contexts, modifiers and triggers, adding the mapping context, and binding actions by ETriggerEvent. Use when wiring movement/look/jump input, creating IA_/IMC_ assets, binding in C++ or Blueprints, or when the user mentions Enhanced Input, Input Mapping Context, Input Action, IA_/IMC_, or ETriggerEvent.

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Compatibility entry point for React-library work in Octane; routes existing-binding maintenance to update-bindings and actual React implementation ports to octane-react-library-port.

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