M
Michał Wojciech Szcześniak
Researcher at Adam Mickiewicz University in Poznań
Publications - 30
Citations - 2884
Michał Wojciech Szcześniak is an academic researcher from Adam Mickiewicz University in Poznań. The author has contributed to research in topics: Gene & RNA splicing. The author has an hindex of 13, co-authored 25 publications receiving 2188 citations. Previous affiliations of Michał Wojciech Szcześniak include Poznan University of Medical Sciences & Max Delbrück Center for Molecular Medicine.
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A survey of best practices for RNA-seq data analysis
Ana Conesa,Pedro Madrigal,Pedro Madrigal,Sonia Tarazona,David Gomez-Cabrero,Alejandra Cervera,Andrew McPherson,Michał Wojciech Szcześniak,Daniel J. Gaffney,Laura L. Elo,Xuegong Zhang,Ali Mortazavi +11 more
TL;DR: All of the major steps in RNA-seq data analysis are reviewed, including experimental design, quality control, read alignment, quantification of gene and transcript levels, visualization, differential gene expression, alternative splicing, functional analysis, gene fusion detection and eQTL mapping.
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CANTATAdb: A Collection of Plant Long Non-Coding RNAs
TL;DR: An online database of lncRNAs in 10 model plant species is created and their potential roles in splicing modulation and deregulation of microRNA functions are investigated to better characterize them.
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Erratum to: A survey of best practices for RNA-seq data analysis
Ana Conesa,Pedro Madrigal,Pedro Madrigal,Sonia Tarazona,David Gomez-Cabrero,Alejandra Cervera,Andrew McPherson,Michał Wojciech Szcześniak,Daniel J. Gaffney,Laura L. Elo,Xuegong Zhang,Ali Mortazavi +11 more
TL;DR: During editing of the article by Conesa et al.
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HuntMi: an efficient and taxon-specific approach in pre-miRNA identification.
TL;DR: HuntMi represents an effective and flexible tool for identification of new microRNAs in animals, plants and viruses and ROC-select strategy proves to be superior to other methods of dealing with class imbalance problem and can possibly be used in other machine learning classification tasks.
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lncRNA-RNA Interactions across the Human Transcriptome.
TL;DR: A similarity-search based method for transcriptome-wide identification of RNA-RNA interactions was implemented, which enabled us to find 18,871,097 lncRNA-RNA base-pairings in human and showed that the interactions could be involved in processing, stability control and functions of 57,303 transcripts.