no code implementations • 17 Dec 2020 • Stavroula Skylaki, Ali Oskooei, Omar Bari, Nadja Herger, Zac Kriegman
Named Entity Recognition (NER) is the task of identifying and classifying named entities in unstructured text.
no code implementations • 18 Nov 2019 • Ali Oskooei, Sophie Mai Chau, Jonas Weiss, Arvind Sridhar, María Rodríguez Martínez, Bruno Michel
We explore and compare three methods in order to perform unsupervised stress detection: 1) traditional K-Means clustering with engineered time and frequency domain features 2) convolutional autoencoders and 3) long short-term memory (LSTM) autoencoders, both trained on the raw RRI measurements combined with DBSCAN clustering and K-Nearest-Neighbors classification.
no code implementations • 29 Aug 2019 • Jannis Born, Matteo Manica, Ali Oskooei, Joris Cadow, Karsten Borgwardt, María Rodríguez Martínez
The generative process is optimized through PaccMann, a previously developed drug sensitivity prediction model to obtain effective anticancer compounds for the given context (i. e., transcriptomic profile).
1 code implementation • 25 Apr 2019 • Matteo Manica, Ali Oskooei, Jannis Born, Vigneshwari Subramanian, Julio Sáez-Rodríguez, María Rodríguez Martínez
In line with recent advances in neural drug design and sensitivity prediction, we propose a novel architecture for interpretable prediction of anticancer compound sensitivity using a multimodal attention-based convolutional encoder.
1 code implementation • 16 Nov 2018 • Ali Oskooei, Jannis Born, Matteo Manica, Vigneshwari Subramanian, Julio Sáez-Rodríguez, María Rodríguez Martínez
Our models ingest a drug-cell pair consisting of SMILES encoding of a compound and the gene expression profile of a cancer cell and predicts an IC50 sensitivity value.
no code implementations • 18 Aug 2018 • Ali Oskooei, Matteo Manica, Roland Mathis, Maria Rodriguez Martinez
We present the Network-based Biased Tree Ensembles (NetBiTE) method for drug sensitivity prediction and drug sensitivity biomarker identification in cancer using a combination of prior knowledge and gene expression data.