Eduardo Andrés-León, PhD, Institute of Parasitology and Biomedicine López-Neyra (IPBLN) and Spanish National Research Institute (CSIC), Spain
Xiangtao Li, PhD, Jilin University, China
BMC Bioinformatics is welcoming submissions to our Collection on RNA-seq data analysis. This Collection welcomes submissions on the development of new computational and/or statistical approaches for the analysis of RNA-seq data.
Eduardo Andrés-León, PhD, Institute of Parasitology and Biomedicine López-Neyra (IPBLN) and Spanish National Research Institute (CSIC), Spain
Dr Andrés-León is the head of the Bioinformatics Unit at the Institute of Parasitology and Biomedicine “López-Neyra,” part of the Spanish National Research Council. He earned his PhD at the Spanish Cancer Research Centre under the mentorship of Prof Alfonso Valencia and Dr Ana Rojas. Dr Andrés-León's funded projects focus on developing algorithms and new methodologies that integrate cutting-edge technologies into clinical practice. His research encompasses single-cell and spatial transcriptomics studies in complex diseases such as cancer, autoimmune disorders, and neurodegenerative diseases. Additionally, he is a member of GESTALT (Global Alliance for Spatial Technologies), Cyted (Ibero-American Programme of Science and Technology for Development) and part of the executive committee of the Spanish Society of Bioinformatics and Computational Biology (SEBiBC).
Xiangtao Li, PhD, Jilin University, ChinaDr Xiangtao Li serves as a Professor at the School of Artificial Intelligence, Jilin University, Jilin, China. His expertise spans the realms of bioinformatics, computational biology, artificial intelligence, single-cell RNA-seq, and protein-RNA binding. His group focuses on employing advanced deep learning techniques to decode complex biological and biomedical datasets, such as single-cell RNA-seq, multi-omics, and spatial transcriptomics. By harnessing state-of-the-art deep learning algorithms, Dr Li has developed methods to cluster cells from single-cell RNA sequencing data. Venturing further into multi-omics and spatial transcriptomics, Dr Li and his group strive to uncover the intricate molecular layers within cells, shedding light on the spatial intricacies of transcriptional processes.
BMC Bioinformatics is welcoming submissions to our Collection on RNA-seq data analysis.
RNA sequencing (RNA-seq) provides comprehensive insights into the transcriptome of a cell, and over the years, it has evolved to enable the study of single-cell expression, translation, non-coding RNA, and RNA-RNA interactions. RNA-seq has become an indispensable tool for understanding gene expression regulation, discovering novel transcripts, and elucidating alternative splicing events. Additionally, RNA-seq plays a crucial role in the study of diseases, allowing researchers to identify disease-associated gene expression patterns, uncover dysregulated pathways, and discover potential biomarkers or therapeutic targets, thereby advancing our understanding of disease mechanisms and aiding in the development of precision medicine.
This Collection welcomes submissions on the development of new computational and/or statistical approaches for the analysis of RNA-seq data.
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