Skill UI

Python bindings to OpenMS for computational mass spectrometry. Analyze proteomics and metabolomics LC-MS/MS data: feature detection, peptide and protein identification, label-free and isobaric quantification, adduct and accurate-mass annotation, plus ready-to-run workflow scripts.

Prepares bulk RNA-seq FASTQ and Salmon, STAR or featureCounts output for gene-level differential expression. Covers nf-core/rnaseq, replication, strandedness, count assembly and a PyDESeq2 handoff.

This skill helps authors determine if their research, which focuses on the complex interface between agricultural management and environmental outcomes, is appropriate for the journal 'Agriculture, Ecosystems & Environment.' It details the required scope, from greenhouse gas fluxes and biodiversity to soil and water quality at the field-to-landscape scale, emphasizing the necessity of environmental outcome quantification and sound ecological methodology.

A specialized tool for polishing pure mathematics manuscripts, designed to enhance the rigor and overall flow of academic writing. It guides authors to eliminate soft language (e.g., "clearly," "obviously"), ensure precise quantification, explicitly state constant dependencies, and structure hypotheses meticulously. Ideal for late-stage proof refinement before journal submission.

Outlines the mandatory and highly structured STAR Methods reporting format required by top-tier scientific journals. This guide details the five critical sections: Key Resources Table (KRT), Resource Availability, Experimental Model Details, Method Details, and Quantification & Statistical Analysis (QSA). Adherence to this structure ensures transparent, reproducible, and accessible scientific reporting.

A comprehensive guide for executing and reporting robust statistical analyses for manuscripts in Global Change Biology (GCB). This skill ensures the analysis meets the high standards of reproducibility required for publicly archived data (DOI). It covers advanced methods including mixed/hierarchical modeling, time-series and spatial analysis, meta-analysis, and rigorous uncertainty quantification (parameter, structural, and scenario). It emphasizes statistical rigor over result fabrication, guiding the use of appropriate inferential machinery based on data structure.

A comprehensive style guide for structuring and refining robotics research manuscripts for top-tier conferences like ICRA. It dictates moving from technique-speak to task-first narratives, emphasizing figure-first presentation, rigorous quantification of claims, and adhering to strict page budgets to maximize reviewer impact and clarity.

This guide provides comprehensive instructions for structuring and refining manuscripts intended for IMFER, ensuring the prose resonates with both academic referees and policy readers. It covers the structure of the introduction, the format of the abstract (including JEL codes and italicization), and maintains consistency in style, tone, and quantification.

A guide for advanced data analysis in policy evaluation, extending beyond standard causal estimates. It emphasizes rigorous reporting of cost-benefit ratios, distributional consequences (who gains and who pays), robust heterogeneity testing, and honest uncertainty quantification necessary for high-level policy academic journals. Essential for turning effect sizes into decision-relevant policy narratives.

This guide provides comprehensive methodology for advanced empirical analysis in Public Economics, particularly for manuscripts using large administrative or register microdata. It covers advanced topics like estimating behavioral elasticities, calculating welfare metrics (MVPF, DWL), and ensuring robust causal identification strategies. It emphasizes translating raw coefficients into policy-relevant quantities with rigorous uncertainty quantification.

This skill assesses the suitability and required rigor of a manuscript for the Molecular Biology and Evolution journal. It provides comprehensive guidelines covering specific scopes (e.g., population genetics, phylogenetics, positive selection), necessary methodological standards (including uncertainty quantification and addressing selection bias), and structural requirements for high-impact submissions in molecular evolution and genomics.

A comprehensive guide for authors submitting to Nature Geoscience, detailing best practices for selecting suggested and excluded referees. It teaches how to strategically write the manuscript and cover letter to preemptively address common high-impact journal objections regarding scientific breadth, technical grounding, and uncertainty quantification.