Results 51 to 60 of about 98,849 (283)

Mapping the evolution of mitochondrial complex I through structural variation

FEBS Letters, EarlyView.
Respiratory complex I (CI) is crucial for bioenergetic metabolism in many prokaryotes and eukaryotes. It is composed of a conserved set of core subunits and additional accessory subunits that vary depending on the organism. Here, we categorize CI subunits from available structures to map the evolution of CI across eukaryotes. Respiratory complex I (CI)
Dong‐Woo Shin, Tingting Chen, James A. Letts   +2 more
wiley   +1 more source

An Unsupervised Band Selection Method via Contrastive Learning for Hyperspectral Images

Remote Sensing, 2023
Band selection (BS) is an efficacious approach to reduce hyperspectral information redundancy while preserving the physical meaning of hyperspectral images (HSIs).
Xiaorun Li, Yufei Liu, Ziqiang Hua, Shuhan Chen   +3 more
doaj   +1 more source

Phenotypic subtyping via contrastive learning

, 2023
AbstractDefining and accounting for subphenotypic structure has the potential to increase statistical power and provide a deeper understanding of the heterogeneity in the molecular basis of complex disease. Existing phenotype subtyping methods primarily rely on clinically observed heterogeneity or metadata clustering.
Aditya Gorla, Sriram Sankararaman, Esteban Burchard, Jonathan Flint, Noah Zaitlen, Elior Rahmani   +5 more
openaire   +2 more sources

Adiabatic Persistent Contrastive Divergence learning [PDF]

2017 IEEE International Symposium on Information Theory (ISIT), 2017
22 pages, 2 ...
Jang, Hyeryung, Choi, Hyungwon, Yi, Yung, Shin, Jinwoo   +3 more
openaire   +2 more sources

Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system

FEBS Letters, EarlyView.
Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley   +1 more source

PDCNet: A Polarimetric Data-Enhanced Contrastive Learning Network for PolSAR Land Cover Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Polarimetric synthetic aperture radar (PolSAR) has rich polarization information, offering an efficient and reliable means of collecting information. However, how to effectively leverage these complex data to extract polarization features remains a key ...
Bo Ren, Chaoyue Hua, Biao Hou, Jian Lv, Chen Yang, Licheng Jiao, Jocelyn Chanussot   +6 more
doaj   +1 more source

In vitro models of cancer‐associated fibroblast heterogeneity uncover subtype‐specific effects of CRISPR perturbations

Molecular Oncology, EarlyView.
Development of therapies targeting cancer‐associated fibroblasts (CAFs) necessitates preclinical model systems that faithfully represent CAF–tumor biology. We established an in vitro coculture system of patient‐derived pancreatic CAFs and tumor cell lines and demonstrated its recapitulation of primary CAF–tumor biology with single‐cell transcriptomics ...
Elysia Saputra, Shamsudheen Karuthedath Vellarikkal, Lixia Li, Hong Sun, Khoa Nguyen, Amber Montano, Suchitra Natarajan, Federica Piccioni, Alex Michael Tamburino, Xin Yu, Aleksandra Katarzyna Olow   +10 more
wiley   +1 more source

Investigating Contrastive Pair Learning’s Frontiers in Supervised, Semisupervised, and Self-Supervised Learning

Journal of Imaging
In recent years, contrastive learning has been a highly favored method for self-supervised representation learning, which significantly improves the unsupervised training of deep image models. Self-supervised learning is a subset of unsupervised learning
Bihi Sabiri, Amal Khtira, Bouchra El Asri, Maryem Rhanoui   +3 more
doaj   +1 more source

Conditional Restricted Boltzmann Machines for Structured Output Prediction [PDF]

, 2011
Conditional Restricted Boltzmann Machines (CRBMs) are rich probabilistic models that have recently been applied to a wide range of problems, including collaborative filtering, classification, and modeling motion capture data. While much progress has been
Hinton, Geoffrey E., Larochelle, Hugo, Mnih, Volodymyr   +2 more
core   +1 more source

NormFace: L2 Hypersphere Embedding for Face Verification

, 2017
Thanks to the recent developments of Convolutional Neural Networks, the performance of face verification methods has increased rapidly. In a typical face verification method, feature normalization is a critical step for boosting performance.
Cheng, Jian, Wang, Feng, Xiang, Xiang, Yuille, Alan L.   +3 more
core   +1 more source