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This Parse Biosciences and bit.bio alliance combines single-cell RNA sequencing and causal transcriptomics to map transcription factor-driven cell identity, enabling improved disea...
RNA sequencing supports space biology research by enabling transcriptome-wide analysis of gene expression changes associated with spaceflight and adaptation to space environments.....
by Anyi Yang, Xingzhong Zhao, Xing-Ming Zhao, Yucheng T. Yang Reconstructing causality routes from genetic effects to complex phenotypes in particular cell types is crucial for un...
A new blood-test platform enables noninvasive monitoring of gene expression in living tissues over time, complementing RNA sequencing approaches for studying disease progression......
by Alda Sabalic, Victoria Moiseeva, Andres Cisneros, Oleg Deryagin, Eusebio Perdiguero, Pura Muñoz-Cánoves, Jordi Garcia-Ojalvo Identifying the genetic correlates of complex pheno...
MERCURIUSâ„¢ 1536 DRUG-seq brings RNA sequencing to large-scale compound screening, enabling efficient gene expression profiling... The post Alithea Genomics launches early access...
RNA sequencing with regRNA Capture-seq identified thousands of regulatory RNAs and enabled new strategies to increase expression of disease-related genes using ASOs...
by Yushi Tang, John D. Storey We recently developed a causal inference framework and test—the Transmission Mean Test (TMT)—to identify causal genotype–phenotype relationships in p...
by Yu-Wen Hsu, Yu-Ning Lu, Mingming Liu, Jiou Wang Neurodegenerative disorders including amyotrophic lateral sclerosis (ALS) remain largely unsolved, with complex etiology yet to...
by Haihan Zhang, Kevin He, Lam C. Tsoi, Xiang Zhou Recent advances in transcriptome-wide association study (TWAS) fine-mapping have enabled the joint modeling of multiple genes to...
by Md Istiaq Ansari, Khandakar Tanvir Ahmed, Debby D. Wang, Kirill Medvedev, Wei Zhang Protein isoforms produced from the same gene through post-transcriptional regulatory mechani...
RNA sequencing from more than 22 million cells trained a model that predicts cell-type-specific gene expression and noncoding variant...
This collection highlights how RNA sequencing is advancing transcriptomics research, from single-cell analysis and disease mechanisms to nanopore sequencing and AI-driven data inte...
A new APA-seq analysis method improves differential gene expression detection, helping researchers gain deeper insights from RNA sequencing data and alternative polyadenylation stu...
by Alexander Rakowski, Christoph Lippert Identifying causal genetic variants in a computational manner remains an open problem. Training end-to-end prediction models is not possib...
TAP-seq combines genome editing with targeted RNA sequencing to enable sensitive and cost-effective single-cell functional genomics screens...
A new study compares two prevailing models, cuprizone (CPZ) and lysophosphatidylcholine (LPC), to reveal new insights into myelin loss and regeneration in a MS mouse model. The po...
RNA sequencing using nanopore direct RNA sequencing enables simultaneous analysis of native RNA molecules, transcript isoforms, RNA modifications, and poly(A) tails for comprehensi...
by Zhaotong Lin, Wei Pan, Haoran Xue Inferring a causal network among multiple traits is essential for unraveling complex biological relationships and informing interventions. Men...
RNA sequencing combined with high-throughput functional profiling enabled researchers to build complete riboswitch models and uncover coordinated structural changes involved in gen...
by Joseph T. Benthal, Justin A. Avila, Jeffrey R. Smith, E. Michelle Southard-Smith Hirschsprung disease (HSCR) is characterized by absence of enteric ganglia (aganglionosis) alon...
by Zachary Hemminger, Haley De Ocampo, Fangming Xie, Zhiqian Zhai, Jingyi Jessica Li, Roy Wollman Motivation Most imaging-based spatial transcriptomics methods measure individual g...
In the intricate landscape of genetic regulation, the study of RNA-binding proteins is unraveling new dimensions of molecular control mechanisms pivotal for development and disease...
A 2026 paper reports on an AI trained on genomic data, including data from a 2024 paper, enabling it to predict when transcription would be initiated. Source
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