Michael Jendrusch,Jan O Korbel
Michael Jendrusch
Proteins play diverse roles in all domains of life and are extensively harnessed as biomolecules in biotechnology, with applications spanning from fundamental research to biomedicine. Therefore, there is considerable interest in computation...
Simon Deltadahl,Julian Gilbey,Christine Van Laer et al.
Simon Deltadahl et al.
Blood cell morphology assessment via light microscopy constitutes a cornerstone of haematological diagnostics, providing crucial insights into diverse pathological conditions. This complex task demands expert interpretation owing to subtle ...
Generating 3D Binding Molecules Using Shape-Conditioned Diffusion Models with Guidance [0.03%]
基于形状的指导扩散模型生成3D结合分子
Ziqi Chen,Bo Peng,Tianhua Zhai et al.
Ziqi Chen et al.
Drug development is a critical but notoriously resource- and time-consuming process. In this manuscript, we develop a novel generative artificial intelligence (genAI) method DiffSMol to facilitate drug development. DiffSMol generates 3D bin...
Johannes Y Lee,Sangjoon Lee,Abhishek Mishra et al.
Johannes Y Lee et al.
Motor brain-computer interfaces (BCIs) decode neural signals to help people with paralysis move and communicate. Even with important advances in the past two decades, BCIs face a key obstacle to clinical viability: BCI performance should st...
Yan C Leyva,Marcelo D T Torres,Carlos A Oliva et al.
Yan C Leyva et al.
Computational protein and peptide design is emerging as a transformative framework for engineering macromolecules with precise structures and functions, offering innovative solutions in medicine, biotechnology and materials science. However...
Single-unit activations confer inductive biases for emergent circuit solutions to cognitive tasks [0.03%]
单个神经元激活赋予认知任务中涌现回路解决方案的归纳偏差
Pavel Tolmachev,Tatiana A Engel
Pavel Tolmachev
Trained recurrent neural networks (RNNs) have become the leading framework for modelling neural dynamics in the brain, owing to their capacity to mimic how population-level computations arise from interactions among many units with heteroge...
Resolving data bias improves generalization in binding affinity prediction [0.03%]
解决数据偏差可提高结合亲和力预测的泛化性能
David Graber,Peter Stockinger,Fabian Meyer et al.
David Graber et al.
The field of computational drug design requires accurate scoring functions to predict binding affinities for protein-ligand interactions. However, train-test data leakage between the PDBbind database and the Comparative Assessment of Scorin...
Predicting the conformational flexibility of antibody and T cell receptor complementarity-determining regions [0.03%]
抗体和T细胞受体互补决定区构象柔韧性的预测
Fabian C Spoendlin,Monica L Fernández-Quintero,Sai S R Raghavan et al.
Fabian C Spoendlin et al.
Many proteins are highly flexible and their ability to adapt their shape can be fundamental to their functional properties. For example, the flexibility of antibody complementarity-determining region (CDR) loops influences binding affinity ...
Reusability report: Leveraging supervised learning to uncover phenotype-relevant biology from single-cell RNA sequencing data [0.03%]
基于单细胞RNA测序数据的监督学习再利用报告：揭示与表型相关的生物学规律
Yingying Cao,Tian-Gen Chang,Sahil Sahni et al.
Yingying Cao et al.
Recent advances in single-cell transcriptome sequencing and computational analysis methods have improved our understanding of cellular heterogeneity. However, associating different cell subsets with phenotypes remains challenging. Recently,...
Error-controlled non-additive interaction discovery in machine learning models [0.03%]
可控的机器学习模型中非加性相互作用的发现算法
Winston Chen,Yifan Jiang,William Stafford Noble et al.
Winston Chen et al.
Machine learning (ML) models are powerful tools for detecting complex patterns, yet their 'black-box' nature limits their interpretability, hindering their use in critical domains like healthcare and finance. Interpretable ML methods aim to...