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PaperPlayer biorxiv bioinformatics

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PoMeLo: a systematic computational approach to...

PaperPlayer biorxiv bioinformatics ·

2023/08/03

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.08.01.551502v1?rss=1 Authors: Glascock, A. L., Waltari, E., Dudas, G., Wong, J., Ahyong, V. Abstract: Background: Genome streamlining, the process by which genomes become smaller and encode fewer genes over time, is a common phenomenon among pathogenic bacteria. This reduction is driven by selection for faster replication and minimized energy expenditure in a nutrient-rich environment. As pathogens evolve to become more reliant on

Non-sequential alignment of binding sites for fast...

PaperPlayer biorxiv bioinformatics ·

2023/08/03

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.08.01.551496v1?rss=1 Authors: GUYON, F., Moroy, G. Abstract: Motivation: Peptides are molecules involved in many essential biological activities by interacting with proteins in the body. They can also be used as therapeutic molecules, particularly to disrupt protein-protein interactions involved in disease. However, it is difficult to identify potential therapeutic peptides if the structure of the protein-protein complex to be

The importance of DNA sequence for nucleosome...

PaperPlayer biorxiv bioinformatics ·

2023/08/03

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.08.01.550795v1?rss=1 Authors: Sahrhage, M., Paul, N. B., Beissbarth, T., Haubrock, M. Abstract: Nucleosome positioning is a key factor in the regulation of transcription, as nucleosomes regulate the dynamic accessibility of chromatin for transcription factor binding and interact with the transcription machinery at every stage. Influences to steer nucleosome positioning are diverse, and the importance of the DNA sequence for this

Unraveling the Pathogenesis of Idiopathic Pulmonary...

PaperPlayer biorxiv bioinformatics ·

2023/08/02

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.31.551395v1?rss=1 Authors: Xu, Z. Abstract: Background: Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive lung disease characterized by excessive scarring of lung tissue. Recent studies have indicated a potential link between IPF and type 2 diabetes (T2D), suggesting that T2D may contribute to the pathogenesis of IPF or vice versa. In this study, we aim to investigate the underlying molecular mechanisms and

MousiPLIER: A Mouse Pathway-Level Information...

PaperPlayer biorxiv bioinformatics ·

2023/08/02

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.31.551386v1?rss=1 Authors: Zhang, S., Heil, B. J., Mao, W., Greene, C. S., Heller, E. A. Abstract: High throughput gene expression profiling is a powerful approach to generate hypotheses on the underlying causes of biological function and disease. Yet this approach is limited by its ability to infer underlying biological pathways and burden of testing tens of thousands of individual genes. Machine learning models that

NetActivity enhances transcriptional signals by...

PaperPlayer biorxiv bioinformatics ·

2023/08/02

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.31.551238v1?rss=1 Authors: Ruiz-Arenas, C., Marin-Goni, I., Wang, L., Ochoa, I., Perez-Jurado, L. A., Hernaez, M. Abstract: Background/Objectives: Grouping gene expression into gene set activity scores (GSAS) provides better biological insights than studying individual genes. However, existing gene set projection methods cannot return representative, robust, and interpretable GSAS. Methods: We developed NetActivity, a machine

SR2: Sparse Representation Learning for Scalable...

PaperPlayer biorxiv bioinformatics ·

2023/08/02

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.31.551228v1?rss=1 Authors: ZHAO, K., SO, H.-C., Lin, Z. Abstract: Single-cell RNA-sequencing (scRNA-seq) technology has been widely used to measure the transcriptome of cells in complex and heterogeneous systems. Integrative analysis of multiple scRNA-seq data can transform our understanding of various aspects of biology at the single-cell level. Many computational methods are proposed for data integration. However, few methods

ProjectSVR: Mapping single-cell RNA-seq data to...

PaperPlayer biorxiv bioinformatics ·

2023/08/02

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.31.551202v1?rss=1 Authors: Gao, J., Guo, S., Zhang, Y. Abstract: The rapid accumulation of public single-cell RNA-seq (scRNA-seq) data and advances in integration algorithms make it possible to build the organ and body-scale cell atlases after overcoming the batch effect originating from different studies, donors, and sequence platforms. However, projecting the query cells onto the carefully constructed reference atlas to

Machine Learning Gene Signature to Metastatic ccRCC...

PaperPlayer biorxiv bioinformatics ·

2023/08/02

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.31.551358v1?rss=1 Authors: de Farias Filho, E. D., Stransky, B., Terrematte, P. C. A. Abstract: Renal carcinoma is a pathology of silent and multifactorial development characterized by a high rate of metastases in patients. After several studies have elucidated the activity of coding genes in the metastatic progression of renal carcinoma, new studies seek to evaluate the association of non-coding genes, such as competitive

Unveiling a Potential Prognostic Biomarker in...

PaperPlayer biorxiv bioinformatics ·

2023/08/02

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.31.551246v1?rss=1 Authors: Dodin, Y. Abstract: Background: Globally, lung cancer is the leading cause of cancer-related deaths, primarily non-small cell lung cancer (NSCLC). Kirsten Rat Sarcoma Oncogene Homolog (KRAS) mutations are common in NSCLC and linked to a poor prognosis. Covalent inhibitors targeting KRAS-G12C mutation have improved treatment for some patients, but most KRAS-mutant lung adenocarcinoma (KRAS-MT LUAD)

A systematic comparison of computational methods for...

PaperPlayer biorxiv bioinformatics ·

2023/07/31

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.28.551039v1?rss=1 Authors: Kernfeld, E. M., Yang, Y., Weinstock, J. S., Battle, A., Cahan, P. M. Abstract: Due to the abundance of single cell RNA-seq data, a number of methods for predicting expression after perturbation have recently been published. Expression prediction methods are enticing because they promise to answer pressing questions in fields ranging from developmental genetics to cell fate engineering and because they

NetVA: An R Package for Network Vulnerability and...

PaperPlayer biorxiv bioinformatics ·

2023/07/31

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.31.551200v1?rss=1 Authors: Kumar, S., Pauline, G., Vindal, V. Abstract: In biological network analysis, identifying key molecules plays a decisive role in the development of potential diagnostic and therapeutic candidates. Among various approaches of network analysis, network vulnerability analysis is quite important, as it assesses significant associations between topological properties and the functional essentiality of a

Model-based compound hypothesis testing for...

PaperPlayer biorxiv bioinformatics ·

2023/07/31

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.30.551108v1?rss=1 Authors: Miao, Z., Wang, J., Park, K., Kuang, D., Kim, J. Abstract: Single nucleus ATAC-seq (snATAC-seq) experimental designs have become increasingly complex with multiple factors that might affect chromatin accessibility, including cell type, tissue of origin, sample location, batch, etc., whose compound effects are difficult to test by existing methods. In addition, current snATAC-seq data present

disperseNN2: a neural network for estimating...

PaperPlayer biorxiv bioinformatics ·

2023/07/31

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.30.551115v1?rss=1 Authors: Smith, C. C., Kern, A. D. Abstract: Summary: We present a deep learning tool, disperseNN2, for estimating the mean per-generation dispersal distance from georeferenced polymorphism data. Our neural network performs feature extraction on pairs of genotypes, and uses the geographic information that comes with each sample. These attributes led disperseNN2 to outperform a state-of-the-art deep learning

A diversified, widespread microbial gene cluster...

PaperPlayer biorxiv bioinformatics ·

2023/07/31

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.31.551370v1?rss=1 Authors: Kountz, D. J., Balskus, E. P. Abstract: Analyses of microbial genome sequencing data have revealed unexpectedly wide distributions of enzymes from specialized metabolic pathways, including enzymes from methanogens, providing exciting opportunities for discovery. Here, we identify a family of gene clusters (the type 1 mlp gene clusters (MGCs)) that encodes homologs of the soluble coenzyme M

The Role of C-to-U RNA Editing in Human Biodiversity

PaperPlayer biorxiv bioinformatics ·

2023/07/31

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.31.550344v1?rss=1 Authors: Van Norden, M. C., Falls, Z., Mandloi, S., Segal, B., Baysal, B., Samudrala, R., Elkin, P. L. Abstract: Intra-organism biodiversity is thought to arise from epigenetic modification of our constituent genes and post-translational modifications after mRNA is translated into proteins. We have found that post-transcriptional modification, also known as RNA editing, is also responsible for a significant

ISMI-VAE: A Deep Learning Model for Classifying...

PaperPlayer biorxiv bioinformatics ·

2023/07/31

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.28.550985v1?rss=1 Authors: Li, H., Wang, Y., Lai, Y., Zeng, F., Yang, F. Abstract: Various studies have linked several diseases, including cancer and Covid-19, to single nucleotide variations (SNV). Although scRNA-seq technology can provide SNV and gene expression data, few studies have integrated and analyzed these multimodal data. To address this issue, this paper introduces Interpretable Single-cell Multimodal Data

Picky with peakpicking: assessing chromatographic...

PaperPlayer biorxiv bioinformatics ·

2023/07/30

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.28.551024v1?rss=1 Authors: Kumler, W. E., Hazelton, B. J., Ingalls, A. E. Abstract: Chromatographic peakpicking continues to represent a significant bottleneck in automated LC-MS workflows. Uncontrolled false discovery rates and the lack of manually-calibrated quality metrics require researchers to visually evaluate individual peaks, requiring large amounts of time and breaking replicability. This problem is exacerbated in noisy

Unraveling cell differentiation mechanisms through...

PaperPlayer biorxiv bioinformatics ·

2023/07/30

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.28.551057v1?rss=1 Authors: Flores-Bautista, E., Thomson, M. Abstract: Understanding the circuits that control cell differentiation is a fundamental problem in developmental biology. Single-cell RNA sequencing has emerged as a powerful tool for investigating this problem. However, the reconstruction of developmental trajectories is based on the assumption that cell states traverse a tree-like structure, which may bias our

Transfer learning to leverage larger datasets for...

PaperPlayer biorxiv bioinformatics ·

2023/07/30

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.27.550881v1?rss=1 Authors: Dieckhaus, H., Brocidiacono, M., Randolph, N., Kuhlman, B. Abstract: Amino acid mutations that lower a protein's thermodynamic stability are implicated in numerous diseases, and engineered proteins with enhanced stability are important in research and medicine. Computational methods for predicting how mutations perturb protein stability are therefore of great interest. Despite recent advancements

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