Traversing Chemical Space with Active Deep Learning: A Computational Framework for Low-data Drug Discovery

Data from LitPCBA used in the publication: https://chemrxiv.org/engage/chemrxiv/article-details/65d8833ce9ebbb4db9098cb

Code, data, and measurements for the paper "A Hitchhiker's Guide to Deep Chemical Language Processing for Bioactivity Prediction"

The code used to produce the results in the paper "A Hitchhiker's Guide to Deep Chemical Language Processing for Bioactivity Prediction" is presented. Data and results of all experiments accompany the code for full reproducibility

Dataset for Effect of matrix solidification on the structure formation in electromagnetic suspensions

Dataset from numerical simulations describing the structure formation in suspensions with electromagnetically active particles in an external field, as described in detail in the paper Konstantinos Manikas, Markus Hütter, Patrick D. Anderson: Effect of matrix solidification on the structure formation in electromagnetic suspensions. Appl. Phys. A, 128: 709 (11 pages), 2022. DOI: 10.1007/s00339-022-05844-y WWW: https://doi.org/10.1007/s00339-022-05844-y which should be cited whenever this dataset is used. The data compiled here is the basis for figures 4, 5, and 6 in that paper

Traversing Chemical Space with Active Deep Learning for Low-data Drug Discovery

Raw and processed data from LitPCBA used in the paper "Traversing Chemical Space with Active Deep Learning for Low-data Drug Discovery

Supporting material and code for "Chemical Language Modeling with Structured State Space Models"

Supporting material of the paper: Özçelik R et al. 2024 "Chemical Language Modeling with Structured State Spaces." ChemRxiv (2024). This folder contains the original code (at the time of publication), model weights, generated molecules, source data, and computed log-likelihoods to allow reproducing our results. If you are searching for a code version that is regularly maintained, you can have a look at our GitHub repository

Source data for the publication: Curved Surfaces Induce Metachronal Motion of Microscopic Magnetic Cilia

This data set contains the source data of the publication: Cui, Z., Islam, T. ul, Wang, Y. & Toonder, J.M.J. den (2024). Curved surfaces induce metachronal motion of microscopic magnetic cilia. ACS Appl. Mater. Interfaces. https://doi.org/10.1021/acsami.4c06884. In this paper, we present a novel elegant method that induces metachronal motion of arrays of identical microscopic magnetic artificial cilia by applying a simple rotating uniform magnetic field. The key idea of our method is to place arrays of cilia on surfaces with a specially designed curvature. This results in consecutive cilia experiencing different magnetic field directions at each point in time, inducing a phase lag in their motion, thereby causing collective wave-like motion. We characterize the local flow patterns generated by the motion of the cilia, revealing the formation of vortical patterns. The data are experimentally obtained with methods described in the publication

Micro-topographies induce epigenetic reprogramming and quiescence in human mesenchymal stem cells

Biomaterials can control cell and nuclear morphology. Since the shape of the nucleus influences chromatin architecture, gene expression, and cell identity, surface topography can control cell phenotype. This study explores how surface topography influences nuclear morphology, histone modifications, and expression of histone-associated proteins through advanced histone mass spectrometry and microarray analysis. We found that nuclear confinement is associated with loss of both histone acetylation and nucleoli abundance, while pathway analysis revealed a substantial reduction in gene expression associated with chromosome organization. In light of previous observations where we found a decrease in proliferation and metabolism induced by micro-topographies, we connect these findings with a quiescent phenotype in mesenchymal stem cells, as further shown by a reduction of ribosomal proteins and the maintenance of multipotency on micro-topographies after long-term culture conditions. Furthermore, this influence of micro-topographies on nuclear morphology and proliferation was reversible, as shown by a full return of proliferation when re-cultured on a flat surface. Our findings provide novel insights on how biophysical signaling influences nuclear organization and subsequent cellular phenotype

Source data for the publication: On-demand microfluidic mixing by actuating integrated magnetic microwalls

This data set contains the source data of the publication: Stef Broeren, Inês Figueiredo Pereira, Tongsheng Wang, Jaap den Toonder, Ye Wang. On-demand microfluidic mixing by actuating integrated magnetic microwalls. Lab on a Chip 2023,23, 1524-1530. DOI https://doi.org/10.1039/D2LC01168A. We demonstrated an on-demand micromixer based on the actuation of magnetic microwalls. The data are experimentally obtained with methods described in the publication

Source data for the publication: Miniaturized metachronal magnetic artificial cilia

This data set contains the source data of the publication: Cui, Z., Wang, Y., Zhang, S., Wang, T. & Toonder, J.M.J. den (2023). Self-cleaning surfaces realized by biologically sized magnetic artificial cilia. PNAS 2023, Vol. 120, No. 35, e2304519120. https://doi.org/10.1073/pnas.2304519120. In this study, we introduce a concept that generates metachronal motion of magnetic artificial cilia (MAC), even though the MAC are all identical, and the applied external magnetic field is uniform. This is achieved by integrating a paramagnetic substructure in the substrate underneath the MAC. Uniquely, we can create both symplectic and antiplectic metachrony by changing the relative positions of MAC and substructure. We demonstrate the flow generation of the two metachronal motions in both high and low Reynolds number conditions. The data are experimentally obtained with methods described in the publication

Source data for the publication: Enhancement of microalgae growth using magnetic artificial cilia

This data set contains the source data of the publication: Verburg, T. H. C. M., Schaap, A. M., Zhang, S., den Toonder, J. M. J., & Wang, Y. (2021). Enhancement of microalgae growth using magnetic artificial cilia. Biotechnology and Bioengineering. https://doi.org/10.1002/bit.27756. In this study, we fabricated magnetic artificial cilia (MAC) and implemented them in millimeter scale culture wells and conducted growth experiments with Scenedesmus subspicatus while actuating the MAC in a rotating magnetic field to create flow and mixing. In addition, surface of MAC was made hydrophilic using plasma treatment and its effect on growth was compared with untreated, hydrophobic MAC. The experiments showed that the growth was enhanced by ten and two times with hydrophobic and hydrophilic MAC, respectively, compared with control groups which contain no MAC. The data are experimentally obtained with methods described in the publication