FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4362672701> ?p ?o ?g. }

• W4362672701 abstract "Late-stage drug development failures are usually a consequence of ineffective targets. Thus, proper target identification is needed, which may be possible using computational approaches. The reason being, effective targets have disease-relevant biological functions, and omics data unveil the proteins involved in these functions. Also, properties that favor the existence of binding between drug and target are deducible from the protein’s amino acid sequence. In this work, we developed OncoRTT, a deep learning (DL)-based method for predicting novel therapeutic targets. OncoRTT is designed to reduce suboptimal target selection by identifying novel targets based on features of known effective targets using DL approaches. First, we created the “OncologyTT” datasets, which include genes/proteins associated with ten prevalent cancer types. Then, we generated three sets of features for all genes: omics features, the proteins’ amino-acid sequence BERT embeddings, and the integrated features to train and test the DL classifiers separately. The models achieved high prediction performances in terms of area under the curve (AUC), i.e., AUC greater than 0.88 for all cancer types, with a maximum of 0.95 for leukemia. Also, OncoRTT outperformed the state-of-the-art method using their data in five out of seven cancer types commonly assessed by both methods. Furthermore, OncoRTT predicts novel therapeutic targets using new test data related to the seven cancer types. We further corroborated these results with other validation evidence using the Open Targets Platform and a case study focused on the top-10 predicted therapeutic targets for lung cancer." @default.
• W4362672701 created "2023-04-07" @default.
• W4362672701 creator A5006656166 @default.
• W4362672701 creator A5009607229 @default.
• W4362672701 creator A5016213975 @default.
• W4362672701 creator A5044474509 @default.
• W4362672701 creator A5073587968 @default.
• W4362672701 creator A5085529612 @default.
• W4362672701 creator A5086374617 @default.
• W4362672701 date "2023-04-06" @default.
• W4362672701 modified "2023-09-30" @default.
• W4362672701 title "OncoRTT: Predicting novel oncology-related therapeutic targets using BERT embeddings and omics features" @default.
• W4362672701 cites W1480911578 @default.
• W4362672701 cites W1491553314 @default.
• W4362672701 cites W1966751442 @default.
• W4362672701 cites W1976526581 @default.
• W4362672701 cites W2000196730 @default.
• W4362672701 cites W2009313526 @default.
• W4362672701 cites W2081837827 @default.
• W4362672701 cites W2082331198 @default.
• W4362672701 cites W2087466582 @default.
• W4362672701 cites W2089226872 @default.
• W4362672701 cites W2097289205 @default.
• W4362672701 cites W2099536767 @default.
• W4362672701 cites W2132820240 @default.
• W4362672701 cites W2137297899 @default.
• W4362672701 cites W2153804545 @default.
• W4362672701 cites W2158485828 @default.
• W4362672701 cites W2162813583 @default.
• W4362672701 cites W2219377896 @default.
• W4362672701 cites W2230320310 @default.
• W4362672701 cites W2232931642 @default.
• W4362672701 cites W2291025194 @default.
• W4362672701 cites W2520714212 @default.
• W4362672701 cites W2547330766 @default.
• W4362672701 cites W2557530941 @default.
• W4362672701 cites W2592111475 @default.
• W4362672701 cites W2611299681 @default.
• W4362672701 cites W2615066396 @default.
• W4362672701 cites W2619634539 @default.
• W4362672701 cites W266360251 @default.
• W4362672701 cites W2749454676 @default.
• W4362672701 cites W2753633147 @default.
• W4362672701 cites W2762459254 @default.
• W4362672701 cites W2767593474 @default.
• W4362672701 cites W2896278697 @default.
• W4362672701 cites W2915074980 @default.
• W4362672701 cites W2918849193 @default.
• W4362672701 cites W2923370700 @default.
• W4362672701 cites W2949342052 @default.
• W4362672701 cites W2951934944 @default.
• W4362672701 cites W2953008890 @default.
• W4362672701 cites W2966590054 @default.
• W4362672701 cites W2970358232 @default.
• W4362672701 cites W2978511610 @default.
• W4362672701 cites W2980354659 @default.
• W4362672701 cites W2980396873 @default.
• W4362672701 cites W2982521190 @default.
• W4362672701 cites W2987928072 @default.
• W4362672701 cites W2989848927 @default.
• W4362672701 cites W2991479679 @default.
• W4362672701 cites W2998462049 @default.
• W4362672701 cites W3011200991 @default.
• W4362672701 cites W3013434491 @default.
• W4362672701 cites W3023613719 @default.
• W4362672701 cites W3027758757 @default.
• W4362672701 cites W3031003892 @default.
• W4362672701 cites W3038540837 @default.
• W4362672701 cites W3039465695 @default.
• W4362672701 cites W3101215053 @default.
• W4362672701 cites W3106143834 @default.
• W4362672701 cites W3112376646 @default.
• W4362672701 cites W3116278528 @default.
• W4362672701 cites W3126639583 @default.
• W4362672701 cites W3128646645 @default.
• W4362672701 cites W3131121088 @default.
• W4362672701 cites W3131901903 @default.
• W4362672701 cites W3134831039 @default.
• W4362672701 cites W3154038392 @default.
• W4362672701 cites W3157437194 @default.
• W4362672701 cites W3157876196 @default.
• W4362672701 cites W3158721075 @default.
• W4362672701 cites W3177500196 @default.
• W4362672701 cites W3179970855 @default.
• W4362672701 cites W3189995823 @default.
• W4362672701 cites W3191368886 @default.
• W4362672701 cites W3196892661 @default.
• W4362672701 cites W3197868832 @default.
• W4362672701 cites W3201477029 @default.
• W4362672701 cites W3211726996 @default.
• W4362672701 cites W3214729651 @default.
• W4362672701 cites W4220872781 @default.
• W4362672701 cites W4225498452 @default.
• W4362672701 cites W4234157358 @default.
• W4362672701 cites W4286471529 @default.
• W4362672701 doi "https://doi.org/10.3389/fgene.2023.1139626" @default.
• W4362672701 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37091791" @default.
• W4362672701 hasPublicationYear "2023" @default.
• W4362672701 type Work @default.
• W4362672701 citedByCount "0" @default.

• next