8 citations · 9 across the 4 of their papers we have counts for
4 papers
Securing Dual-Use Pathogen Data of Concern
Doni Bloomfield, Allison Berke, Moritz S. Hanke +6
Training data is an essential input into creating competent artificial intelligence (AI) models. AI models for biology are trained on large volumes of data, including data related…
Open-weight genome language model safeguards: Assessing robustness via adversarial fine-tuning
James R. M. Black, Moritz S. Hanke, Aaron Maiwald +3
Novel deep learning architectures are increasingly being applied to biological data, including genetic sequences. These models, referred to as genomic language models (gLMs), have…
Comprehensive Overview of Bottom-up Proteomics using Mass Spectrometry
Yuming Jiang, Devasahayam Arokia Balaya Rex, Dina Schuster +16
Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up…
Deep metric learning improves lab of origin prediction of genetically engineered plasmids
Igor M. Soares, Fernando H. F. Camargo, Adriano Marques +1
Genome engineering is undergoing unprecedented development and is now becoming widely available. To ensure responsible biotechnology innovation and to reduce misuse of engineered D…