AIMC Journal:
International journal of molecular sciences

Showing 381 to 390 of 423 articles

Quantitative Structure-Activity Relationships for Structurally Diverse Chemotypes Having Anti- Activity.

International journal of molecular sciences Jun 8, 2019
Small-molecule compounds that have promising activity against macromolecular targets from occasionally fail when tested in whole-cell phenotypic assays. This outcome can be attributed to many factors, including inadequate physicochemical and pharmac...
Machine Learning Quantitative Structure-Activity Relationship Trypanosoma cruzi Trypanocidal Agents
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A Structure-Based Drug Discovery Paradigm.

International journal of molecular sciences Jun 6, 2019
Structure-based drug design is becoming an essential tool for faster and more cost-efficient lead discovery relative to the traditional method. Genomic, proteomic, and structural studies have provided hundreds of new targets and opportunities for fut...
Drug Discovery Molecular Docking Simulation Deep Learning Quantitative Structure-Activity Relationship
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Analysis of Expression Pattern of snoRNAs in Different Cancer Types with Machine Learning Algorithms.

International journal of molecular sciences May 2, 2019
Small nucleolar RNAs (snoRNAs) are a new type of functional small RNAs involved in the chemical modifications of rRNAs, tRNAs, and small nuclear RNAs. It is reported that they play important roles in tumorigenesis via various regulatory modes. snoRNA...
Machine Learning Algorithms Neoplasms Humans Monte Carlo Method RNA, Small Nucleolar Gene Expression Regulation, Neoplastic Support Vector Machine
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Exploring the Potential of Spherical Harmonics and PCVM for Compounds Activity Prediction.

International journal of molecular sciences May 2, 2019
Biologically active chemical compounds may provide remedies for several diseases. Meanwhile, Machine Learning techniques applied to Drug Discovery, which are cheaper and faster than wet-lab experiments, have the capability to more effectively identif...
Databases, Protein Receptors, G-Protein-Coupled Machine Learning Algorithms Drug Discovery Support Vector Machine Animals Humans
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Deep Learning/Artificial Intelligence and Blood-Based DNA Epigenomic Prediction of Cerebral Palsy.

International journal of molecular sciences Apr 27, 2019
The etiology of cerebral palsy (CP) is complex and remains inadequately understood. Early detection of CP is an important clinical objective as this improves long term outcomes. We performed genome-wide DNA methylation analysis to identify epigenomic...
Humans Infant, Newborn Gene Expression Profiling Artificial Intelligence Epigenomics DNA Methylation CpG Islands Gene Regulatory Networks Cell-Free Nucleic Acids Case-Control Studies Cerebral Palsy ROC Curve Epigenesis, Genetic Deep Learning
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mACPpred: A Support Vector Machine-Based Meta-Predictor for Identification of Anticancer Peptides.

International journal of molecular sciences Apr 22, 2019
Anticancer peptides (ACPs) are promising therapeutic agents for targeting and killing cancer cells. The accurate prediction of ACPs from given peptide sequences remains as an open problem in the field of immunoinformatics. Recently, machine learning ...
Antineoplastic Agents ROC Curve Reproducibility of Results Chemical Phenomena Peptides Web Browser Humans Software Support Vector Machine
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A Deep Learning Approach to the Screening of Oncogenic Gene Fusions in Humans.

International journal of molecular sciences Apr 2, 2019
Gene fusions have a very important role in the study of cancer development. In this regard, predicting the probability of protein fusion transcripts of developing into a cancer is a very challenging and yet not fully explored research problem. To thi...
Algorithms Deep Learning Probability Humans Neural Networks, Computer Oncogene Fusion
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RPITER: A Hierarchical Deep Learning Framework for ncRNA⁻Protein Interaction Prediction.

International journal of molecular sciences Mar 1, 2019
Non-coding RNAs (ncRNAs) play crucial roles in multiple fundamental biological processes, such as post-transcriptional gene regulation, and are implicated in many complex human diseases. Mostly ncRNAs function by interacting with corresponding RNA-bi...
Sequence Analysis, Protein Protein Binding Sequence Analysis, RNA RNA, Long Noncoding Humans Software Machine Learning Animals
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BGFE: A Deep Learning Model for ncRNA-Protein Interaction Predictions Based on Improved Sequence Information.

International journal of molecular sciences Feb 23, 2019
The interactions between ncRNAs and proteins are critical for regulating various cellular processes in organisms, such as gene expression regulations. However, due to limitations, including financial and material consumptions in recent experimental m...
Computational Biology Software Databases, Protein Deep Learning Amino Acid Sequence RNA, Untranslated ROC Curve Position-Specific Scoring Matrices Protein Binding
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Prediction of Self-Interacting Proteins from Protein Sequence Information Based on Random Projection Model and Fast Fourier Transform.

International journal of molecular sciences Feb 21, 2019
It is significant for biological cells to predict self-interacting proteins (SIPs) in the field of bioinformatics. SIPs mean that two or more identical proteins can interact with each other by one gene expression. This plays a major role in the evolu...
Protein Binding Support Vector Machine Binding Sites Sequence Analysis, Protein Fourier Analysis Saccharomyces cerevisiae Proteins Humans Animals
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