A5009240058- Protein Structure and Dynamics
- Machine Learning in Bioinformatics
- Genetics and Neurodevelopmental Disorders
- Galaxies: Formation, Evolution, Phenomena
- Library Collection Development and Digital Resources
- Enzyme Structure and Function
- Hedgehog Signaling Pathway Studies
- Advanced Vision and Imaging
- Climate variability and models
- Ubiquitin and proteasome pathways
- Probabilistic and Robust Engineering Design
- Library Science and Information Literacy
- Advanced Image Processing Techniques
- Hyperglycemia and glycemic control in critically ill and hospitalized patients
- Genomics and Rare Diseases
- Cancer Research and Treatments
- Geology and Paleoclimatology Research
- Cancer Immunotherapy and Biomarkers
- Gaussian Processes and Bayesian Inference
- Astronomical Observations and Instrumentation
- Colorectal Cancer Treatments and Studies
- Scientific Research and Discoveries
- Computational Drug Discovery Methods
- Chromatin Remodeling and Cancer
- Control Systems and Identification
Google (United Kingdom)
2024
DeepMind (United Kingdom)
2021-2024
University of California, Santa Cruz
2019-2021
Translational Genomics Research Institute
2007-2009
University of Toledo
1992
Abstract Proteins are essential to life, and understanding their structure can facilitate a mechanistic of function. Through an enormous experimental effort 1–4 , the structures around 100,000 unique proteins have been determined 5 but this represents small fraction billions known protein sequences 6,7 . Structural coverage is bottlenecked by months years painstaking required determine single structure. Accurate computational approaches needed address gap enable large-scale structural...
Abstract The introduction of AlphaFold 2 1 has spurred a revolution in modelling the structure proteins and their interactions, enabling huge range applications protein design 2–6 . Here we describe our 3 model with substantially updated diffusion-based architecture that is capable predicting joint complexes including proteins, nucleic acids, small molecules, ions modified residues. new demonstrates improved accuracy over many previous specialized tools: far greater for protein–ligand...
Abstract Protein structures can provide invaluable information, both for reasoning about biological processes and enabling interventions such as structure-based drug development or targeted mutagenesis. After decades of effort, 17% the total residues in human protein sequences are covered by an experimentally determined structure 1 . Here we markedly expand structural coverage proteome applying state-of-the-art machine learning method, AlphaFold 2 , at a scale that covers almost entire...
We describe the operation and improvement of AlphaFold, system that was entered by team AlphaFold2 to "human" category in 14th Critical Assessment Protein Structure Prediction (CASP14). The AlphaFold CASP14 is entirely different one CASP13. It used a novel end-to-end deep neural network trained produce protein structures from amino acid sequence, multiple sequence alignments, homologous proteins. In assessors' ranking summed z scores (>2.0), scored 244.0 compared 90.8 next best group....
Abstract To establish well‐characterized cellular reagents for the study of colon carcinoma, we have examined 19 human colorectal carcinoma cell lines with regard to morphology, ultra‐structure, expression tumor‐associated antigens, proliferative capacity in vitro , anchorage‐independent growth, oncogene expression, tumorigenicity and malignant potential. Cell were cultured under identical conditions, vivo analyses performed parallel on replicate cultures. Three classes defined according...
Previously, utilizing a series of genome-wide association, brain imaging and gene expression studies we implicated the KIBRA RhoA/ROCK pathway in hippocampal-mediated human memory.Here show that peripheral administration ROCK inhibitor hydroxyfasudil improves spatial learning working memory rodent model.This study supports action on memory, suggests potential value inhibition for promotion cognition humans highlights powerful unbiased association to inform novel uses existing pharmaceuticals.
Near-future large galaxy surveys will encounter blended images at a fraction of up to 50% in the densest regions universe. Current deblending techniques may segment foreground while leaving missing pixel intensities background flux. The problem is compounded by diffuse nature galaxies their outer regions, making segmentation significantly more difficult than traditional object applications. We propose novel branched generative adversarial network (GAN) deblend overlapping galaxies, where two...
We perform an out-of-distribution analysis of ~12,000,000 semi-independent 128x128 pixel^2 SST regions, which we define as cutouts, from all nighttime granules in the MODIS R2019 Level-2 public dataset to discover most complex or extreme phenomena at ocean surface. Our algorithm (Ulmo) is a probabilistic autoencoder, combines two deep learning modules: (1) trained on ~150,000 random cutouts 2010, represent any input cutout with 512-dimensional latent vector akin (non-linear) EOF analysis;...
Measurement of the red damping wing neutral hydrogen in quasar spectra provides a probe epoch reionization early Universe. Such quantification requires precise and unbiased estimates intrinsic continua near Lyman-$α$ (Ly$α$), challenging task given highly variable Ly$α$ emission profiles quasars. Here, we introduce fully probabilistic approach to prediction. We frame problem as conditional density estimation explicitly model distribution over plausible blue-side ($1190\ \unicode{xC5} \leq...
This article examines the University of Toledo Carlson Library's cooperative effort with IBM personnel in attempting to design a new and cost‐effective method for networking CD‐ROM databases. It outlines how development was conceived executed, presents recommendations on such ventures can be effectively carried out future.