Titlebook: Hydrogen Technologies; Reimund Neugebauer Book 2023 Springer Nature Switzerland AG 2023 Renewable energies.Energy storage.Industrial produ

vanquish

Reimund Neugebaueret captures nonlinear effects of multi-omics data to survival outcomes via a neural network framework, while allowing one to biologically interpret the model. In the extensive experiments with multi-omics data of Gliblastoma multiforme (GBM) patients, MiNet outperformed the current cutting-edge meth

Decibel

Simon Harst,Bernhard A?mus,Angelika Hackner,Anja Haslingeris used to calculate the relational initial scores for new drugs. To systematically evaluate the prediction performance of IDNDDI and compare it with other prediction methods, we conduct the 5-fold cross validation and de novo drug validation. In terms of the AUC (area under the ROC curve)value, IDN

CBC471

Martin Wietschel,Elisabeth Dütschke,Marius Neuwirth,Aline Scherrer,Lin Zheng,Norman Gerhardt,Sebastial information. Also, the partner antigen is vital for paratope prediction, and we employ Att-BLSTM on the partner antigen sequence as well. The outputs of CNNs and Att-BLSTM networks are combined to predict antibody paratope by fully-connected networks. The experiments show that our proposed method

出處

Jochen Bard,Norman Gerhardt,Marie Plaisir,Ramona Schr?er,Anne Held,Hans-Martin Henning,Christoph Koso-layer RGCN to predict microbe-disease associations. Compared with other methods, TNRGCN achieves a good performance in cross validation. Meanwhile, case studies for diseases demonstrate TNRGCN has a good performance for predicting potential microbe-disease associations.

Needlework

冒號

Ulf Groos,Malte Semmel,Achim Schaadt,Stefan Bürger,Felix Horch,Johannes Geiling,Richard ?chsner,Gunt.We conducted a series of simulation experiments to assess the performance of . and compared it against previously existing probabilistic methods (.) and parsimonious methods (.). As we learned from the results, . can reconstruct more correct ancestral adjacencies and yet run several orders of magni

音樂學者

Spirometry

Ulrike Herrmann,Natalia Pieton,Benjamin Pfluger,Katharina Alms,Tanja Manuela Kneiske,Christopher VogrRWMDE, takes several steps of random walking on three different biological networks, microRNA-microRNA functional similarity network(MFN), disease-disease similarity network(DSN) and environmental factor similarity network(ESN) respectively so as to get microRNA-disease association information from

甜瓜

Sebastian Metz,Tom Smolinka,Christian I. Bern?cker,Stefan Loos,Thomas Rauscher,Lars R?ntzsch,Michaeleins. It is the same way with S-PIN and NF-APIN. NF-APIN is a dynamic PIN constructed by using gene expression data and S-PIN. The experimental results on the protein interaction network of S.cerevisiae shows that all the six network-based methods achieve better results when being applied on TS-PIN

直覺好

Ulf Groos,Carsten Cremers,Laura Nousch,Christoph Baumg?rtnere true biological mutations. HapIso uses a k-means clustering algorithm aiming to group the reads into two meaningful clusters maximizing the similarity of the reads within cluster and minimizing the similarity of the reads from different clusters. Each cluster corresponds to a parental haplotype. W