Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Johannes, Smolander"'
Autor:
Tanja Buchacher, Ankitha Shetty, Saara A. Koskela, Johannes Smolander, Riina Kaukonen, António G.G. Sousa, Sini Junttila, Asta Laiho, Olof Rundquist, Tapio Lönnberg, Alexander Marson, Omid Rasool, Laura L. Elo, Riitta Lahesmaa
Publikováno v:
Cell Reports, Vol 42, Iss 12, Pp 113469- (2023)
Summary: The serine/threonine-specific Moloney murine leukemia virus (PIM) kinase family (i.e., PIM1, PIM2, and PIM3) has been extensively studied in tumorigenesis. PIM kinases are downstream of several cytokine signaling pathways that drive immune-m
Externí odkaz:
https://doaj.org/article/3a090e9a93c647a8b4fb1957f69538cc
Autor:
Johannes Smolander, Sofia Khan, Kalaimathy Singaravelu, Leni Kauko, Riikka J. Lund, Asta Laiho, Laura L. Elo
Publikováno v:
BMC Genomics, Vol 22, Iss 1, Pp 1-15 (2021)
Abstract Background Detection of copy number variations (CNVs) from high-throughput next-generation whole-genome sequencing (WGS) data has become a widely used research method during the recent years. However, only a little is known about the applica
Externí odkaz:
https://doaj.org/article/dc83a894cd3b4d2189a7798343171802
Publikováno v:
BMC Cancer, Vol 19, Iss 1, Pp 1-15 (2019)
Abstract Background Deciphering the meaning of the human DNA is an outstanding goal which would revolutionize medicine and our way for treating diseases. In recent years, non-coding RNAs have attracted much attention and shown to be functional in par
Externí odkaz:
https://doaj.org/article/19d2fd4b1bb24fba953db4cdaf2340e1
Publikováno v:
FEBS Open Bio, Vol 9, Iss 7, Pp 1232-1248 (2019)
Genomics data provide great opportunities for translational research and the clinical practice, for example, for predicting disease stages. However, the classification of such data is a challenging task due to their high dimensionality, noise, and he
Externí odkaz:
https://doaj.org/article/109a41c78f67404eb85d12e8f50db7a2
Autor:
Tiina Kelkka, Paula Savola, Dipabarna Bhattacharya, Jani Huuhtanen, Tapio Lönnberg, Matti Kankainen, Kirsi Paalanen, Mikko Tyster, Maija Lepistö, Pekka Ellonen, Johannes Smolander, Samuli Eldfors, Bhagwan Yadav, Sofia Khan, Riitta Koivuniemi, Christopher Sjöwall, Laura L. Elo, Harri Lähdesmäki, Yuka Maeda, Hiroyoshi Nishikawa, Marjatta Leirisalo-Repo, Tuulikki Sokka-Isler, Satu Mustjoki
Publikováno v:
Frontiers in Immunology, Vol 12 (2021)
Externí odkaz:
https://doaj.org/article/0ae39758c3764572a874d0ca3de3022f
Autor:
Tiina Kelkka, Paula Savola, Dipabarna Bhattacharya, Jani Huuhtanen, Tapio Lönnberg, Matti Kankainen, Kirsi Paalanen, Mikko Tyster, Maija Lepistö, Pekka Ellonen, Johannes Smolander, Samuli Eldfors, Bhagwan Yadav, Sofia Khan, Riitta Koivuniemi, Christopher Sjöwall, Laura L. Elo, Harri Lähdesmäki, Yuka Maeda, Hiroyoshi Nishikawa, Marjatta Leirisalo-Repo, Tuulikki Sokka-Isler, Satu Mustjoki
Publikováno v:
Frontiers in Immunology, Vol 11 (2020)
Rheumatoid arthritis (RA) is a complex autoimmune disease targeting synovial joints. Traditionally, RA is divided into seropositive (SP) and seronegative (SN) disease forms, the latter consisting of an array of unrelated diseases with joint involveme
Externí odkaz:
https://doaj.org/article/269cd4fa96c4412898c4b325a9f2ac64
Single-cell RNA-sequencing enables cell-level investigation of cell differentiation, which can be modelled using trajectory inference methods. While tremendous effort has been put into designing these methods, inferring accurate trajectories automati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7789b91ab7f88aa5c1d9327e575d811e
https://doi.org/10.1101/2022.09.19.508535
https://doi.org/10.1101/2022.09.19.508535
Publikováno v:
Briefings in Bioinformatics. 23
Single-cell RNA-sequencing (scRNA-seq) enables researchers to quantify transcriptomes of thousands of cells simultaneously and study transcriptomic changes between cells. scRNA-seq datasets increasingly include multisubject, multicondition experiment
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0c2d23dae800c8a0789f03687ade6dbd
https://doi.org/10.1093/bib/bbac286
https://doi.org/10.1093/bib/bbac286
Publikováno v:
Bioinformatics
Motivation Single-cell RNA-seq allows researchers to identify cell populations based on unsupervised clustering of the transcriptome. However, subpopulations can have only subtle transcriptomic differences and the high dimensionality of the data make
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d76d31b7b77b623555742df90230f61b
http://europepmc.org/articles/PMC8150131
http://europepmc.org/articles/PMC8150131
Publikováno v:
Bioinformatics (Oxford, England). 38(5)
Motivation Computational models are needed to infer a representation of the cells, i.e. a trajectory, from single-cell RNA-sequencing data that model cell differentiation during a dynamic process. Although many trajectory inference methods exist, the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd4e68e1d4b569f9143e521f6b84c60f
https://pubmed.ncbi.nlm.nih.gov/34888622
https://pubmed.ncbi.nlm.nih.gov/34888622