17 papers · ranked by Valyu relevance
Nabeel Sarwar, Wilson Gregory, George A. Kevrekidis, Soledad Villar + 1 more
'Bianca Dumitrascu'] Single-cell RNA-seq data allow the quantification of cell type differences across a growing set of biological contexts. However, pinpointing a small subset of genomic features explaining this variability can be ill-defined and computationally intractable. Here we introduce MarkerMap, a generative…
Wilson Gregory, Nabeel Sarwar, George Kevrekidis, Soledad Villar + 1 more
Single-cell RNA-seq data allow the quantification of cell type differences across a growing set of biological contexts. However, pinpointing a small subset of genomic features explaining this variability can be ill-defined and computationally intractable. Here we introduce MarkerMap, a generative model for selecting…
Theresa Maurer, Lennart Purucker, Frank Hutter, Peter Pfaffelhuber + 1 more
While classifiers such as TabPFN (16) and SNIPPER (37) achieve strong intercontinental performance (15), their accuracy in classifying individuals within Europe remains low. One major factor contributing to this limitation is the set of genetic markers used for classification. Marker panels such as the VISAGE Enhanced…
Yusuf Baran, Berat Doğan
Single-Cell RNA sequencing (scRNA-seq) has provided unprecedented opportunities for exploring gene expression and thus uncovering regulatory relationships between genes at the single cell level. However, scRNA-seq relies on isolating cells from tissues. Thus, the spatial context of the regulatory processes is lost. A…
Jeffrey M. Pullin, Davis J. McCarthy
The development of single-cell RNA sequencing (scRNA-seq) has enabled scientists to catalogue and probe the transcriptional heterogeneity of individual cells in unprecedented detail. A common step in the analysis of scRNA-seq data is the selection of so-called marker genes, most commonly to enable the annotation of the…
Jeffrey M. Pullin, Davis J. McCarthy
Background The development of single-cell RNA sequencing (scRNA-seq) has enabled scientists to catalog and probe the transcriptional heterogeneity of individual cells in unprecedented detail. A common step in the analysis of scRNA-seq data is the selection of so-called marker genes, most commonly to enable annotation…
Yutong Sun, Peng Qiu, Ilya Ioshikhes
When analyzing scRNA-seq data containing heterogeneous cell populations, an important task is to select informative marker genes to distinguish various cell clusters and annotate the clusters with biologically meaningful cell types. In existing analysis methods and pipelines, marker genes are typically identified using…
An Wang, Stephanie Hicks, Donald Geman, Laurent Younes
The selection of marker gene panels is critical for capturing the cellular and spatial hetero-geneity in the expanding atlases of single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics data. Most current approaches to marker gene selection operate in a label-based framework, which is inherently limited by…
Katharina Waury
Discovery of novel protein biomarkers for clinical applications is an active research field across a manifold of diseases. Despite some successes and progress, the biomarker development pipeline still frequently ends in failure as biomarker candidates cannot be validated or translated to immunoassays. Selection of…
Natalia Polyakova, Oleg Kandarakov, Alexander Belyavsky, Alexander E. Kalyuzhny
'Alexander E. Kalyuzhny'] Magnetic cell sorting technology stands out because of its speed, simplicity, and ability to process large cell numbers. However, it also suffers from a number of drawbacks, in particular low discrimination power, which results in all-or-none selection outcomes limited to a bulk separation of…
Rumiana Tenchov, Aparna Sapra, Janet Sasso, Krittika Ralhan + 3 more
Cancer is one of the leading causes of death worldwide. Early cancer detection is critical because it can significantly improve treatment outcome thus saving lives, reducing suffering, and lessening psychological and economic burdens. Cancer biomarkers provide varied information about cancer, from early detection of…
Oleg F. Kandarakov, Natalia S. Polyakova, Alexandra V. Petrovskaya, Alexandra V. Bruter + 2 more
'Alexandra V. Bruter' 'Alexander V. Belyavsky' 'Suren Zakian'] At present, the magnetic selection of genetically modified cells is mainly performed with surface markers naturally expressed by cells such as CD4, LNGFR (low affinity nerve growth factor receptor), and MHC class I molecule H-2Kk. The disadvantage of such…
Taban Baghfalaki, Reza Hashemi, Christophe Tzourio, Catherine Helmer + 1 more
Multiple Longitudinal Markers and Competing Risk Outcomes Authors: ['Taban Baghfalaki' 'Reza Hashemi' 'Christophe Tzourio' 'Catherine Helmer' 'Hélène Jacqmin‐Gadda'] Background In clinical and epidemiological research, the integration of longitudinal measurements and time-to-event outcomes is vital for understanding…
Mocheng Li, Baotong Lu, James Cheng, Chenhao Ma
Filtering Approximate Nearest Neighbor (FANN) search is a critical and emerging task for strengthening the query capability of vector databases, supporting applications such as recommendation systems, retrieval-augmented generation (RAG), and agent memory. However, most existing methods are limited to range or label…
M. Johnsson
This paper will argue that one of the biggest challenges for livestock genomics is to make whole-genome sequencing and functional genomics applicable to breeding practice. It discusses potential explanations for why it is so difficult to consistently improve the accuracy of genomic prediction by means of wholegenome…
Authors not listed
This paper addresses the challenges in cell line development (CLD), the lengthy and ambiguous clone screening in upstream biopharmaceutical production. Typically, only a small subset of the later stages of CLD data is used for manually selecting lead clones. Addressing this issue, we introduce a multivariate data…
Nicoletta D'Angelo, Giada Adelfio, Matthias Eckardt
This work proposes $χ^2$-type test statistics to assess different hypotheses on the local structure of an observed marked point pattern. The test statistics is based on the local inhomogeneous extension of the mark-weighted $K$-function to investigate local behaviour of the marked point pattern. The summary statistic…