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http://dx.doi.org/10.1016/j.ajhg.2017.06.003 | DOI Listing |
Adv Sci (Weinh)
January 2025
Department of Molecular Pharmacology, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, Tianjin, 300060, China.
Efficient virtual screening methods can expedite drug discovery and facilitate the development of innovative therapeutics. This study presents a novel transfer learning model based on network target theory, integrating deep learning techniques with diverse biological molecular networks to predict drug-disease interactions. By incorporating network techniques that leverage vast existing knowledge, the approach enables the extraction of more precise and informative drug features, resulting in the identification of 88,161 drug-disease interactions involving 7,940 drugs and 2,986 diseases.
View Article and Find Full Text PDFBr J Radiol
January 2025
Division of Nuclear Medicine and Molecular Imaging Center, Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Theranostics has its roots with the first radioiodine therapy for thyroid diseases in about 80 years ago. More recently the field has experienced a remarkable renascence with the regulatory approval of paired imaging and radiopharmaceutical therapy agents in gastroenteropancreatic neuroendocrine tumors and metastatic castration-resistant prostate cancer that are now employed in routine clinical practice. The momentum is strong for identification and testing of new theranostic agents for use in various cancers and finding new clinical incications of the available agents.
View Article and Find Full Text PDFBioinform Adv
June 2024
Department of Pediatrics and Human Development, Michigan State University, Grand Rapids, MI 49503, United States.
Motivation: Bispecific antibodies (bsAbs) that bind to two distinct surface antigens on cancer cells are emerging as an appealing therapeutic strategy in cancer immunotherapy. However, considering the vast number of surface proteins, experimental identification of potential antigen pairs that are selectively expressed in cancer cells and not in normal cells is both costly and time-consuming. Recent studies have utilized large bulk RNA-seq databases to propose bispecific targets for various cancers.
View Article and Find Full Text PDFSmall
January 2025
College of Physical Science and Technology, Xiamen University, Xiamen, 361005, P. R. China.
Twisted bilayer graphene (TBG) has drawn considerable attention due to its angle-dependent electrical, optical, and mechanical properties, yet preparing and identifying samples at specific angles on a large scale remains challenging and labor-intensive. Here, a data-driven strategy that leverages Raman spectroscopy is proposed in combination with deep learning to rapidly and non-destructively decode and predict the twist angle of TBG across the full angular range. By processing high-dimensional Raman data, the deep learning model extracts hidden information to achieve precise twist angle identification.
View Article and Find Full Text PDFiScience
January 2025
Key Laboratory of Resources Biology and Biotechnology in Western China, Ministry of Education, Provincial Key Laboratory of Biotechnology of Shaanxi Province, the College of Life Sciences, Northwest University, Xi'an 710069, China.
Bacteriophages (phages) are increasingly viewed as a promising alternative for the treatment of antibiotic-resistant bacterial infections. However, the diversity of host ranges complicates the identification of target phages. Existing computational tools often fail to accurately identify phages across different bacterial species.
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