Zobrazeno 1 - 10
of 117
pro vyhledávání: '"Jianzhu Ma"'
Publikováno v:
Advanced Intelligent Systems, Vol 5, Iss 12, Pp n/a-n/a (2023)
Diffractive optical neural networks (DONNs) are emerging as high‐throughput and energy‐efficient hardware platforms to perform all‐optical machine learning (ML) in machine vision systems. However, the current demonstrated applications of DONNs
Externí odkaz:
https://doaj.org/article/2591c4993f0b495a9f2c6e2249faa3dd
Autor:
Zhilin Long, Chengfang Sun, Min Tang, Yin Wang, Jiayan Ma, Jichuan Yu, Jingchao Wei, Jianzhu Ma, Bohan Wang, Qi Xie, Jiaming Wen
Publikováno v:
Cell Discovery, Vol 8, Iss 1, Pp 1-21 (2022)
Abstract The clear cell renal cell carcinoma (ccRCC) microenvironment consists of many different cell types and structural components that play critical roles in cancer progression and drug resistance, but the cellular architecture and underlying gen
Externí odkaz:
https://doaj.org/article/a3850ce41b44494bb52fbf7f5ddef5bd
Publikováno v:
Health Data Science, Vol 2022 (2022)
Externí odkaz:
https://doaj.org/article/405f07dd1e4b457ca7051037b8dca9b3
Autor:
Yubo Shao, Kaikai Zhao, Zhiwen Cao, Zhehao Peng, Xingang Peng, Pan Li, Yijie Wang, Jianzhu Ma
Publikováno v:
Sensors, Vol 22, Iss 11, p 4081 (2022)
It is hard to directly deploy deep learning models on today’s smartphones due to the substantial computational costs introduced by millions of parameters. To compress the model, we develop an ℓ0-based sparse group lasso model called MobilePrune w
Externí odkaz:
https://doaj.org/article/ab1e12fa714847bca0bbf5660a75cf5d
Publikováno v:
Nature Communications, Vol 9, Iss 1, Pp 1-11 (2018)
Informative pathways driving cancer pathogenesis and subtypes can be difficult to identify in the presence of many gene interactions irrelevant to cancer. Here, the authors describe an approach for cancer gene pathway analysis based on key molecular
Externí odkaz:
https://doaj.org/article/23364b3760004de1a37cb9eef7adaa17
Publikováno v:
Sensors, Vol 21, Iss 1, p 104 (2020)
In this paper, we propose AirSign, a novel user authentication technology to provide users with more convenient, intuitive, and secure ways of interacting with smartphones in daily settings. AirSign leverages both acoustic and motion sensors for user
Externí odkaz:
https://doaj.org/article/c22651dfa874408686428d95b83f3f73
Publikováno v:
PLoS Computational Biology, Vol 10, Iss 3, p e1003500 (2014)
Sequence-based protein homology detection has been extensively studied and so far the most sensitive method is based upon comparison of protein sequence profiles, which are derived from multiple sequence alignment (MSA) of sequence homologs in a prot
Externí odkaz:
https://doaj.org/article/5af7307a47024e8695343ecfb15b8e60
Autor:
Inna Dubchak, Sandhya Balasubramanian, Sheng Wang, Meydan Cem, Dinanath Sulakhe, Alexander Poliakov, Daniela Börnigen, Bingqing Xie, Andrew Taylor, Jianzhu Ma, Alex R Paciorkowski, Ghayda M Mirzaa, Paul Dave, Gady Agam, Jinbo Xu, Lihadh Al-Gazali, Christopher E Mason, M Elizabeth Ross, Natalia Maltsev, T Conrad Gilliam
Publikováno v:
PLoS ONE, Vol 9, Iss 12, p e114903 (2014)
An essential step in the discovery of molecular mechanisms contributing to disease phenotypes and efficient experimental planning is the development of weighted hypotheses that estimate the functional effects of sequence variants discovered by high-t
Externí odkaz:
https://doaj.org/article/7a98642da2014259af2beccf0a35c397
Characterizing the interaction conformation between T-cell receptors and epitopes with deep learning
Publikováno v:
Nature Machine Intelligence. 5:395-407
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f3014d7438973b445d008e2a05a1b3d
https://doi.org/10.1038/s42256-023-00634-4
https://doi.org/10.1038/s42256-023-00634-4
Autor:
Minsheng Hao, Jing Gong, Xin Zeng, Chiming Liu, Yucheng Guo, Xingyi Cheng, Taifeng Wang, Jianzhu Ma, Le Song, Xuegong Zhang
Large-scale pretrained models have become foundation models, leading to breakthroughs in natural language processing and related fields. Developing foundation models in life science, aimed at deciphering the "languages" of cells and facilitating biom
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::347bf5069b4088a9ab60cf4fbc21699e
https://doi.org/10.1101/2023.05.29.542705
https://doi.org/10.1101/2023.05.29.542705
