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by Su, Zhenqiang and Labaj, Pawel P and Li, Sheng and Thierry-Mieg, Jean and Thierry-Mieg, Danielle and Shi, Wei and Wang, Charles and Schroth, Gary P and Setterquist, Robert A and Thompson, John F and Jones, Wendell D and Xiao, Wenzhong and Xu, Weihong and Jensen, Roderick V and Kelly, Reagan and Xu, Joshua and Conesa, Ana and Furlanello, Cesare and Gao, Hanlin and Hong, Huixiao and Jafari, Nadereh and Letovsky, Stan and Liao, Yang and Lu, Fei and Oakeley, Edward J and Peng, Zhiyu and Praul, Craig A and Santoyo-Lopez, Javier and Scherer, Aneas and Shi, Tieliu and Smyth, Gordon K and Staedtler, Frank and Sykacek, Peter and Tan, Xin-Xing and Thompson, E. Aubrey and Vandesompele, Jo and Wang, May D and Wang, Jian and Wolfinger, Russell D and Zavadil, Jiri and Auerbach, Scott S and Bao, Wenjun and Binder, Hans and Blomquist, Thomas and Brilliant, Murray H and Bushel, Pierre R and Cain, Weimin and Catalano, Jennifer G and Chang, Ching-Wei and Chen, Tao and Chen, Geng and Chen, Rong and Chierici, Marco and Chu, Tzu-Ming and Clevert, Djork-Arne and Deng, Youping and Derti, Adnan and Devanarayan, Viswanath and Dong, Zirui and Dopazo, Joaquin and Du, Tingting and Fang, Hong and Fang, Yongxiang and Fasold, Mario and Fernandez, Anita and Fischer, Matthias and Furio-Tari, Peo and Fuscoe, James C and Caiment, Florian and Gaj, Stan and Gandara, Jorge and Gao, Huan and Ge, Weigong and Gondo, Yoichi and Gong, Binsheng and Gong, Meihua and Gong, Zhuolin and Green, Bridgett and Guo, Chao and Guo, Lei and Guo, Li-Wu and Hadfield, James and Hellemans, Jan and Hochreiter, Sepp and Jia, Meiwen and Jian, Min and Johnson, Charles D and Kay, Suzanne and Kleinjans, Jos and Lababidi, Samir and Levy, Shawn and Li, Quan-Zhen and Li, Li and Li, Peng and Li, Yan and Li, Haiqing and Li, Jianying and Li, Shiyong and Lin, Simon M and Lopez, Francisco J and ... and SEQC/MAQC-III Consortium
Nature Biotechnology, ISSN 1087-0156, 09/2014, Volume 32, Issue 9, pp. 903 - 914
We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the US Food and Drug Administration. Examining Illumina HiSeq,... 
TRANSCRIPTOME | BIOTECHNOLOGY & APPLIED MICROBIOLOGY | BIAS | GENOME ANNOTATION | DIFFERENTIAL GENE-EXPRESSION | ARRAYS | PCR | Reproducibility of Results | Polymerase Chain Reaction | Sequence Analysis, RNA - standards | RNA sequencing | Genetic research | Methods | Quality control | Quality management | Consortia | Ribonucleic acid--RNA
Journal Article
Bioinformatics, ISSN 1367-4803, 04/2006, Volume 22, Issue 8, pp. 943 - 949
MOTIVATION: We propose a new model-based technique for summarizing high-density oligonucleotide array data at probe level for Affymetrix GeneChips. The new... 
Journal Article
Bioinformatics, ISSN 1367-4803, 11/2007, Volume 23, Issue 21, pp. 2897 - 2902
MOTIVATION: DNA microarray technology typically generates many measurements of which only a relatively small subset is informative for the interpretation of... 
Journal Article
ISSN 2041-6520, 2/2019, Volume 1, Issue 6, pp. 1692 - 171
There has been a recent surge of interest in using machine learning across chemical space in order to predict properties of molecules or design molecules and... 
Journal Article
Bioinformatics (Oxford, England), ISSN 1367-4803, 07/2019, Volume 35, Issue 13, pp. 2309 - 2310
Single-guide RNAs (sgRNAs) targeting the same gene can significantly vary in terms of efficacy and specificity. PAVOOC (Prediction And Visualization of On- and... 
Applications Notes
Journal Article
Chemical Science, ISSN 2041-6520, 2019, Volume 10, Issue 6, pp. 1692 - 1701
There has been a recent surge of interest in using machine learning across chemical space in order to predict properties of molecules or design molecules and... 
CLASSIFICATION | CHEMISTRY, MULTIDISCIPLINARY | SETS
Journal Article
Bioinformatics, ISSN 1367-4803, 04/2006, Volume 22, Issue 8, pp. 943 - 949
Journal Article
ISSN 2041-6520, 6/2018, Volume 9, Issue 24, pp. 5441 - 5451
Deep learning is currently the most successful machine learning technique in a wide range of application areas and has recently been applied successfully in... 
Journal Article
CHEMICAL SCIENCE, ISSN 2041-6520, 09/2019, Volume 10, Issue 34, pp. 8016 - 8024
One of the main challenges in small molecule drug discovery is finding novel chemical compounds with desirable properties. In this work, we propose a novel... 
CHEMISTRY, MULTIDISCIPLINARY | DISCOVERY | DE-NOVO DESIGN
Journal Article
Chemical Science, ISSN 2041-6520, 2018, Volume 9, Issue 24, pp. 5441 - 5451
Journal Article
Bioinformatics, ISSN 1367-4803, 07/2017, Volume 33, Issue 14, pp. i59 - i66
Journal Article
Journal of Chemical Information and Modeling, ISSN 1549-9596, 03/2019, Volume 59, Issue 3, pp. 1163 - 1171
Journal Article
Chemical Science, ISSN 2041-6520, 2018, Volume 9, Issue 24, pp. 5441 - 5451
Deep learning is currently the most successful machine learning technique in a wide range of application areas and has recently been applied successfully in... 
VALIDATION | CLASSIFICATION | DESIGN | DEEP NEURAL-NETWORKS | MODELS | CHEMISTRY, MULTIDISCIPLINARY | Performance prediction | Teaching methods | Artificial intelligence | Bias | Molecular chains | Machine learning
Journal Article