20 papers · ranked by Valyu relevance
Maximilian Willer, Peter Ruckdeschel
It is motivated by the rapidly evolving field of algorithmic fairness — the PhD topic of the first author — where new metrics, mitigation strategies, and machine learning methods continuously emerge. A central challenge in fairness, but also far beyond, is that existing toolkits either focus narrowly on single…
Shixiang Wang
Bioinformatics analyses depend on workflow engines to coordinate dozens of computational tools across complex dependency chains. The most widely adopted engines—Snakemake, Nextflow, the Common Workflow Language (CWL), and the Workflow Description Language (WDL)—run on interpreted or just-in-time (JIT) compiled language…
Fabiana Fournier, Lior Limonad
We introduce the process harness, a new mechanism for uplifting legacy workflows into Agentic Business Process Management (Agentic BPM) without replacing the underlying workflow engine. A process harness places a policy-governed agentic layer around a deterministic workflow engine, intercepting designated control…
Panchal, Deven
—Generative Agentic AI systems are emerging as a powerful paradigm for automating complex, multi-step tasks. However, many existing frameworks for building these systems introduce significant complexity, a steep learning curve, and substantial boilerplate code, hindering rapid prototyping and deployment. This paper…
Dongmin Shin, Jeonghwan Henry Kim, Rakbin Sung, Junil Kim + 2 more
User requests are initiated from a web client built on (, [https://github.com/vuejs/core]()), which relies on Drawflow (, [https://github.com/jerosoler/Drawflow]()) for visual programming and Plotly () for data visualization ([sup1] at Bioinformatics online). The user requests are routed through an NGINX () web server…
Houcheng Su, Junning Feng, Yawen Lu, Yucheng Xu + 10 more
Title: Summary The growing volume and complexity of biological data have made bioinformatics workflows increasingly labor-intensive, error-prone, and difficult to scale. Large language model-based agents offer potential for automation but often fail in complex, multi-step analyses because of limited robustness. We…
Prachi Gupta, William J. Riehl, Mikaela Cashman, Dylan Chivian + 6 more
Constructing multi-step bioinformatics workflows, from read quality control through genome assembly to functional annotation, requires expertise in both biology and computational tool selection, creating a bottleneck for scalable and reproducible analysis. We present the KBase Research Agent, a multi-agent system for…
Authors not listed
Self-driving laboratories (SDLs) promise accelerated scientific discovery and product development by closing the loop between robotic execution and AI/ML-driven decision making. In practice, however, SDL orchestration remains fragmented; workflows are typically encoded as laboratory-specific scripts or bespoke…
Soham Ghosh, Gaurav Mittal
Large language models (LLMs) are powerful in language understanding and content generation but frequently fall short of technical accuracy when they are applied to engineering code, standards, and design documents. To mitigate this, we are seeing the emergence of Retrieval-Augmented Generation (RAG) models that ground…
Kaoudi, Zoi, Giurgiu, Ioana
—The proliferation of large language models (LLMs) has accelerated the adoption of agent-based workflows, where multiple autonomous agents reason, invoke functions, and collaborate to compose complex data pipelines. However, current approaches to building such agentic architectures remain largely ad hoc, lacking…
Alan Seroul, Théo Fagnoni, Inès Adnani, Dana O. Mohamed + 2 more
This paper introduces the Opus Workflow Evaluation Framework, a probabilistic-normative formulation for quantifying Workflow quality and efficiency. It integrates notions of correctness, reliability, and cost into a coherent mathematical model that enables direct comparison, scoring, and optimization of Workflows. The…
Jia Ding, Yun Peng, Ruochen Wei, Boquan Wang + 3 more
BLIT ensures computational reproducibility through robust environment management, built on the lightweight Micromamba engine-the statically linked, self-contained executable version of Mamba. This foundation enables fast dependency resolution with minimal overhead and seamless installation and execution of tools from…
Authors not listed
Agentic artificial intelligence (AI) is poised to redefine how science is conducted, automating not just data analysis but the entire research lifecycle, from hypothesis generation to validation. Yet most current AI agents remain domain-bound, tailored to specific applications such as materials synthesis or quantum…
Ahmed Fadiel, Kenneth D. Eichenbaum, Aya Hassouneh, Kunle Odunsi + 2 more
Using AI to analyze metabolite profiles provides critical insights into health, aging, and disease. Metabolomic signatures reveal how lifestyle and therapy impact organ function and cancer progression. This review highlights emerging toolkits for high-throughput data analysis, emphasizing their integration with other…
Ke Chen, Ziming Chen, Dagang Zheng, Xiang Fang + 7 more
Computational methods have advanced the analysis of animal behavior, yet significant challenges remain in data standardization, analytical reproducibility, and workflow integration. Existing computational solutions often demand extensive programming proficiency or compel users to navigate a highly fragmented ecosystem…
Yingying Zhao, Quanyou Cai, Dongzhu Chen, Jiekai Chen
Datasets in the Gene Expression Omnibus (GEO) remain difficult to reuse at scale because sample annotations are heterogeneous and raw sequencing data require assay-specific preprocessing. We present GEOAgent, an AI-driven autonomous framework designed for intelligent dataset retrieval and standardized preprocessing by…
Caroline Ott, Kevin Schneider, Heinrich Lukas Weil, Florian Wetzels + 3 more
Modern research projects typically involve several measurement techniques and computational analyses, resulting in complex, multimodal research data objects. While the FAIR Principles provide a framework for making data Findable, Accessible, Interoperable, and Reusable, researchers must still apply community standards…
Authors not listed
Realizing the promise of artificial intelligence (AI) to accelerate scientific progress and deliver technological impact depends on how effectively AI can be integrated into real-world decision- making processes. As Peter Norvig states, “Somewhat remarkably, almost all AI research until very recently has assumed that…
Tamara Klymkovych, Nataliia Bokla, Wojciech Zabierowski, Dmytro Klymkovych
An integrated approach for enhancing microparticle separation efficiency in acoustofluidic lab-on-a-chip systems is presented, combining numerical modeling in COMSOL 6.2 Multiphysics® with reinforcement learning techniques implemented in Python 3.10.14. The proposed method addresses the limitations of traditional…
Authors not listed
Process chemistry creates scalable routes for new lead molecules and is a crucial but laborious stage in pharmaceutical and agrochemical development cycles. We have built an automated process chemistry platform that tackles late-stage process development. The modular workflow integrates both industry-standard tools and…