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Cell Cycle Proteins

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Comparison of Selected Parameters of Redox Homeostasis in Patients with Ataxia-Telangiectasia and Nijmegen Breakage Syndrome.

Oxidative medicine and cellular longevity 29456787
This study compared the antioxidant status and major lipophilic antioxidants in patients with ataxia-telangiectasia (AT) and Nijmegen breakage syndrome (NBS). Total antioxidant status (TAS), total oxidant status (TOS), oxidative stress index (OSI), a...
Adolescent Ataxia Telangiectasia Ataxia Telangiectasia Mutated Proteins Cell Cycle Proteins Child Female Homeostasis Humans Male Nijmegen Breakage Syndrome Nuclear Proteins Oxidation-Reduction Oxidative Stress Ubiquinone Vitamin A Vitamin E
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Identification of Cell Cycle-Regulated Genes by Convolutional Neural Network.

Combinatorial chemistry & high throughput screening 28413974
BACKGROUND: The cell cycle-regulated genes express periodically with the cell cycle stages, and the identification and study of these genes can provide a deep understanding of the cell cycle process. Large false positives and low overlaps are big pro...
Algorithms Cell Cycle Proteins Databases, Genetic Neural Networks, Computer Saccharomyces cerevisiae Saccharomyces cerevisiae Proteins
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Machine-Learning-Assisted Approach for Discovering Novel Inhibitors Targeting Bromodomain-Containing Protein 4.

Journal of chemical information and modeling 28636361
Bromodomain-containing protein 4 (BRD4) is implicated in the pathogenesis of a number of different cancers, inflammatory diseases and heart failure. Much effort has been dedicated toward discovering novel scaffold BRD4 inhibitors (BRD4is) with differ...
Cell Cycle Proteins Cell Line Drug Discovery Drug Evaluation, Preclinical Humans Machine Learning Molecular Docking Simulation Molecular Targeted Therapy Nuclear Proteins Protein Conformation Structure-Activity Relationship Transcription Factors
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NNAlign: a platform to construct and evaluate artificial neural network models of receptor-ligand interactions.

Nucleic acids research 28407117
Peptides are extensively used to characterize functional or (linear) structural aspects of receptor-ligand interactions in biological systems, e.g. SH2, SH3, PDZ peptide-recognition domains, the MHC membrane receptors and enzymes such as kinases and ...
Algorithms Amino Acid Sequence Basic Helix-Loop-Helix Leucine Zipper Transcription Factors Binding Sites Cell Cycle Proteins Databases, Protein Forkhead Transcription Factors HLA-A1 Antigen HLA-B7 Antigen HLA-B8 Antigen HLA-DRB1 Chains Humans Internet Ligands Neural Networks, Computer Peptides Protein Binding Sequence Alignment Software Trans-Activators
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DriverML: a machine learning algorithm for identifying driver genes in cancer sequencing studies.

Nucleic acids research 30773592
Although rapid progress has been made in computational approaches for prioritizing cancer driver genes, research is far from achieving the ultimate goal of discovering a complete catalog of genes truly associated with cancer. Driver gene lists predic...
Atlases as Topic Cell Cycle Proteins Cell Line, Tumor Cell Movement Cell Proliferation Datasets as Topic Gene Expression Regulation, Neoplastic Humans Machine Learning Monte Carlo Method Mutation Neoplasm Proteins Neoplasms Nuclear Proteins Oncogenes Software
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Treatment Potential for Macular Cone Vision in Leber Congenital Amaurosis Due to CEP290 or NPHP5 Mutations: Predictions From Artificial Intelligence.

Investigative ophthalmology & visual science 31212307
PURPOSE: To use supervised machine learning to predict visual function from retinal structure in retinitis pigmentosa (RP) and apply these estimates to CEP290- and NPHP5-associated Leber congenital amaurosis (LCA) to determine the potential for funct...
Adolescent Adult Antigens, Neoplasm Calmodulin-Binding Proteins Cell Cycle Proteins Color Vision Defects Cytoskeletal Proteins Female Genetic Therapy Humans Leber Congenital Amaurosis Machine Learning Male Middle Aged Mutation Neoplasm Proteins Retinal Cone Photoreceptor Cells Retinitis Pigmentosa Tomography, Optical Coherence Visual Field Tests Visual Fields Young Adult
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FOLFOX treatment response prediction in metastatic or recurrent colorectal cancer patients via machine learning algorithms.

Cancer medicine 31893575
Early identification of metastatic or recurrent colorectal cancer (CRC) patients who will be sensitive to FOLFOX (5-FU, leucovorin and oxaliplatin) therapy is very important. We performed microarray meta-analysis to identify differentially expressed ...
Antineoplastic Combined Chemotherapy Protocols Biomarkers, Tumor Cell Cycle Proteins Colorectal Neoplasms Datasets as Topic Fluorouracil Gene Expression Profiling Gene Expression Regulation, Neoplastic Humans Intracellular Signaling Peptides and Proteins Leucovorin Machine Learning Neoplasm Recurrence, Local Oligonucleotide Array Sequence Analysis Organoplatinum Compounds Prognosis Protein Kinases Response Evaluation Criteria in Solid Tumors
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DeepMILO: a deep learning approach to predict the impact of non-coding sequence variants on 3D chromatin structure.

Genome biology 32216817
Non-coding variants have been shown to be related to disease by alteration of 3D genome structures. We propose a deep learning method, DeepMILO, to predict the effects of variants on CTCF/cohesin-mediated insulator loops. Application of DeepMILO on v...
CCCTC-Binding Factor Cell Cycle Proteins Cell Line, Tumor Chromatin Chromosomal Proteins, Non-Histone Cohesins Deep Learning Humans Insulator Elements Mutation Neoplasms Whole Genome Sequencing
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Predicting 3D genome folding from DNA sequence with Akita.

Nature methods 33046897
In interphase, the human genome sequence folds in three dimensions into a rich variety of locus-specific contact patterns. Cohesin and CTCF (CCCTC-binding factor) are key regulators; perturbing the levels of either greatly disrupts genome-wide foldin...
CCCTC-Binding Factor Cell Cycle Proteins Chromosomal Proteins, Non-Histone Cohesins DNA-Binding Proteins Gene Expression Regulation Genome, Human Humans Models, Genetic Neural Networks, Computer Sequence Analysis, DNA
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Artificial intelligence grading of breast cancer: a promising method to refine prognostic classification for management precision.

Histopathology 33590486
AIM: Artificial intelligence (AI)-based breast cancer grading may help to overcome perceived limitations of human assessment. Here, the potential value of AI grade was evaluated at the molecular level and in predicting patient outcome.
Artificial Intelligence ATPases Associated with Diverse Cellular Activities Biomarkers, Tumor Breast Neoplasms Cell Cycle Proteins Cohort Studies Databases as Topic Female Humans Image Interpretation, Computer-Assisted Neoplasm Grading Precision Medicine Prognosis Survival Analysis Treatment Outcome
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