“downstream”的搜索结果

Build whole-genome alignments using Progressive Cactus (Armstrong 2020 reference-free clade-level WGA), Minigraph-Cactus (Hickey 2024 pangenome-aware), LASTZ chain/net (UCSC pipeline), MUMmer4 (Marçais 2018 pairwise), minimap2 -x asm5/10/20 (Li 2018 fast pairwise), AnchorWave (Song 2022 WGD-aware), and Mauve / progressiveMauve (bacterial). Operates the HAL toolkit (Hickey 2013) for downstream extraction including halSynteny, halLiftover, halBranchMutations, and hal2maf. Use when constructing multi-species alignments for comparative-annotation projection (TOGA), synteny detection, conservation analyses (phyloP / PhastCons), or pangenome graph construction; selecting between reference-free (Cactus) and reference-anchored (LASTZ chains/nets) approaches; tuning sensitivity for closely vs distantly related genomes; or producing HAL files for genome-wide downstream tools.

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Cascade merge changes through a chain of dependent branches. Use when updating stacked/chained PRs, propagating changes from a parent branch to all downstream branches, or when the user mentions "cascade merge", "propagate changes", "update dependent branches", or "merge to downstream branches".

中文简介正在准备中。当前显示原文说明。

Build whole-genome alignments using Progressive Cactus (Armstrong 2020 reference-free clade-level WGA), Minigraph-Cactus (Hickey 2024 pangenome-aware), LASTZ chain/net (UCSC pipeline), MUMmer4 (Marçais 2018 pairwise), minimap2 -x asm5/10/20 (Li 2018 fast pairwise), AnchorWave (Song 2022 WGD-aware), and Mauve / progressiveMauve (bacterial). Operates the HAL toolkit (Hickey 2013) for downstream extraction including halSynteny, halLiftover, halBranchMutations, and hal2maf. Use when constructing multi-species alignments for comparative-annotation projection (TOGA), synteny detection, conservation analyses (phyloP / PhastCons), or pangenome graph construction; selecting between reference-free (Cactus) and reference-anchored (LASTZ chains/nets) approaches; tuning sensitivity for closely vs distantly related genomes; or producing HAL files for genome-wide downstream tools.

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将Paperclip的Storybook界面示例与实际产品及功能清单对照，整理数据、分类和引用，保留示例标识与链接，并区分当前功能示例、原型和历史探索。

• 在界面变更后维护展示示例
• 更新模拟数据与API响应
• 分类原型和历史界面示例

将审核通过的成果交接到CLI、代码智能体、Figma等指定工作环境，并在成果管理信息中追加输出目标，保留此前的分发历史。

• 将已审核成果交给代码智能体
• 将编辑结果写回原Figma文件
• 通过GitHub的PR交付成果

将笔记、转写文本或文档整理成推动听众理解的演讲结构，规划每页的图片、图表、视频及制作说明，并在渲染后最多进行三轮核对，提出修改要求。

• 根据笔记或转写文本组织演讲
• 规划每页的图片、图表与视频
• 编写HTML幻灯片或PPTX制作说明

Send a single request to DeepSeek for summarization, information extraction, or simple classification. Receive the response and token usage as JSON for further processing, with structured status information when the API is unavailable.

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• Summarizing text in a single request
• Extracting information from text
• Classifying text into simple categories

Dry-run one cycle of a sales agent workflow without calling language models. Validate the template and agent types, check budget reservations, generate agent prompts, and record a structured status summary for downstream automation.

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• Demonstrating one cycle of a sales agent workflow
• Checking template validity and agent types
• Verifying budget caps and reservations

Inspect FCS files from flow cytometry, a method for measuring cell properties, using FlowIO. Extract measurement data into NumPy arrays, review channel metadata, export tables, and create FCS 3.1 files for downstream work.

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• Inspect measurement settings and channel labels in FCS files
• Extract measurement data into NumPy arrays or CSV tables
• Read legacy FCS files containing multiple datasets

Prepare bulk RNA-seq sequencing files or quantification outputs for gene-level comparisons. Check sample information and data quality, configure processing workflows, and assemble validated count tables and metadata for downstream differential expression analysis with PyDESeq2.

中文简介正在准备中。当前显示英语简介。

• Preparing gene count tables from FASTQ files
• Configuring an nf-core/rnaseq workflow
• Combining Salmon, STAR, or featureCounts outputs

Analyze encrypted ZIP challenges in a CTF sandbox and use bkcrack to recover legacy ZipCrypto keys from known file contents. Create a decrypted archive, validate extraction, and preserve the commands and evidence needed to reproduce the result.

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• Identify the encryption used by a ZIP archive
• Recover ZipCrypto keys from known file contents
• Validate and extract a decrypted archive

Trace server-side request forgery, where a server fetches a supplied URL, through internal services and metadata endpoints in a CTF sandbox. Document credential scope and distinguish successful token extraction from access actually accepted by another service.

中文简介正在准备中。当前显示英语简介。

• Tracing server-side requests to internal services
• Checking metadata access and token scope
• Distinguishing token extraction from accepted access

Solve sandboxed CTF security challenges by reconstructing encoding and encryption steps, extracting data hidden in media, and tracing mobile app signing or storage behavior. Preserve exact parameters and evidence to reproduce decoded content or signed requests.

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• Reconstructing encoding and encryption chains in CTF challenges
• Extracting data hidden in images and other media
• Tracing APK or IPA request-signing logic

Examine Windows credential material in a CTF sandbox, including LSASS memory and Kerberos tickets. Distinguish stored secrets from credentials that actually work, and document the evidence linking their source to successful authentication or resulting privileges.

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• Examining LSASS secrets and Windows logon sessions
• Checking whether recovered Kerberos tickets are usable
• Tracing DPAPI and SSP credential material

Analyze running iOS apps in a CTF sandbox, a controlled challenge environment. Trace methods, inspect secure storage, and examine request signing and certificate checks to identify the state needed to reproduce an accepted request.

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• Trace Objective-C or Swift methods
• Inspect Keychain and local app storage
• Examine certificate checks and request signing

Organize CTF investigations by mapping the supplied targets, tracing one minimal path, and selecting the relevant specialist workflow. Findings are grounded in observed behavior and reproducible evidence, with a clean baseline used for verification.

中文简介正在准备中。当前显示英语简介。

• Choosing an analysis path for a CTF challenge
• Tracing a minimal path through challenge infrastructure
• Packaging reproducible evidence for a solution

Trace software artifacts from source and dependencies through builds, publishing, and runtime use in CTF sandboxes. Compare intended versions with shipped files to identify the earliest divergence and document the evidence linking each stage.

中文简介正在准备中。当前显示英语简介。

• Comparing declared, resolved, and shipped dependency versions
• Tracing package or build tampering through CI/CD
• Identifying the artifact actually used at runtime

Reconstruct frontend behavior from served JavaScript, build manifests, and source maps, which link built code to source. Trace loaded modules, recover route and API references, and identify the smallest asset sequence that explains observed behavior.

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• Reconstructing the structure of served JavaScript
• Recovering route and API references from built assets
• Tracing chunk loading and obscured loader code

Trace SSH keys, tokens, and other credentials in Linux CTF environments. Connect each recovered artifact to the service that accepts it, then document the resulting privileges or movement to another host.

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• Trace where recovered SSH keys and tokens are accepted
• Document privilege gains through sockets or sudo
• Explain movement between Linux challenge hosts

Trace movement between Windows hosts in a CTF sandbox using credentials and Kerberos tickets, which carry authentication information. Connect recovered artifacts to the service that accepted them and document the resulting access or privileges.

中文简介正在准备中。当前显示英语简介。

• Trace movement between Windows hosts
• Identify services that accept recovered credentials
• Connect Kerberos tickets to resulting access

Trace OAuth and OIDC sign-in flows in a CTF sandbox, from redirects through token exchange to application acceptance. Show where tokens become a recognized identity or permission, and preserve the smallest reproducible flow.

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• Trace sign-in redirects and callback parameters
• Inspect state, nonce, and PKCE validation
• Check how tokens become application identity or permissions

Analyze packet captures in a CTF sandbox by rebuilding communication sessions and decoding message contents. Recover transferred files and connect packet order, timing, and reconstructed streams to observed host or malware behavior.

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• Rebuild TCP or UDP communication sessions
• Decode HTTP, DNS, or custom protocol messages
• Recover files transferred over the network

Build an evidence-backed incident timeline in a CTF sandbox by correlating logs, network captures, and other artifacts. Trace attacker actions across sources, distinguish confirmed events from inferred gaps, and preserve the sequence that supports the conclusion.

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• Combine logs and network captures into an incident timeline
• Trace attacker actions from initial access to persistence
• Separate confirmed event order from inferred gaps

Trace mailbox abuse in a CTF sandbox, a controlled security challenge environment. The skill connects OAuth permissions, forwarding rules, delegated access, and message logs to concrete mail effects, documenting the smallest reproducible sequence and supporting evidence.

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• Trace how OAuth consent enables mailbox access
• Investigate forwarding and inbox rule effects
• Verify shared mailbox and delegated access