Project description:Transcriptional profiles of U2 OS cell line treated with ~21 thousands of compounds from diversity-oriented-synthesis (DOS) library.

2014-05-30 | LDS-1194 | LINCS

iMN (Exp 2) - ALS, SMA and Control (unaffected) iMN cell lines differentiated from iPS cell lines using a long differentiation protocol - RNA-seq

Project description:Total RNA-Seq was carried out on rRNA depleted RNA obtained from motor neuron lines generated from subject induced pluripotent stem cell (iPSC) lines. The iPSC lines were derived from 4 ALS, 3 SMA and 3 Control (unaffected) individuals, in duplicate.

2017-05-01 | LDS-1398 | LINCS

Random-primed mRNA-sequencing transcriptomic dataset for 70 primary human cardiomyocyte cell samples

Project description:Each of 70 cell samples either at the control condition or treated with FDA-approved cancer drugs is sequenced by the single-ended random-primed mRNA-sequencing method with a read length of 100 base pairs, and a total of 70 raw sequence data files in the FASTQ format are generated. These sequence data files are then analyzed by a high-performance computational pipeline and ranked lists of gene signatures and biological processes related to drug-induced cardiotoxicity are generated for each drug. The raw sequence datasets and the analysis results have been carefully controlled for data quality, and they are made publicly available at the Gene Expression Omnibus (GEO) database repository of NIH. As such, this broad drug-stimulated transcriptomi dataset is valuable for the prediction of drug toxicities and their mitigations.

2020-11-09 | LDS-1587 | LINCS

3'-DGE mRNA-sequencing transcriptomic dataset for 914 primary human cardiomyocyte cell samples

Project description:Each of 914 cell samples either at the control condition or treated with FDA-approved cancer drugs is sequenced by the single-ended 3'-DGE mRNA-sequencing method with a read length of 46 base pairs, and a total of 914 raw sequence data files in the FASTQ format are generated. These sequence data files are then analyzed by a high-performance computational pipeline and ranked lists of gene signatures and biological processes related to drug-induced cardiotoxicity are generated for each drug. The raw sequence datasets and the analysis results have been carefully controlled for data quality, and they are made publicly available at the Gene Expression Omnibus (GEO) database repository of NIH. As such, this broad drug-stimulated transcriptomi dataset is valuable for the prediction of drug toxicities and their mitigations.

2020-11-09 | LDS-1592 | LINCS

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