Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou׳ s general PseAAC
Protein subcellular localization is defined as predicting the functioning location of a given
protein in the cell. It is considered an important step towards protein function prediction and …
protein in the cell. It is considered an important step towards protein function prediction and …
Massive datasets and machine learning for computational biomedicine: trends and challenges
This survey paper attempts to cover a broad range of topics related to computational
biomedicine. The field has been attracting great attention due to a number of benefits it can …
biomedicine. The field has been attracting great attention due to a number of benefits it can …
The linear neighborhood propagation method for predicting long non-coding RNA–protein interactions
Long non-coding RNAs (lncRNAs) have gained wide attentions because of their essential
functions in a variety of biological processes. Though precise functions and mechanisms of …
functions in a variety of biological processes. Though precise functions and mechanisms of …
Accurate single-sequence prediction of protein intrinsic disorder by an ensemble of deep recurrent and convolutional architectures
Recognizing the widespread existence of intrinsically disordered regions in proteins spurred
the development of computational techniques for their detection. All existing techniques can …
the development of computational techniques for their detection. All existing techniques can …
Crop production-ensemble machine learning model for prediction
N Balakrishnan… - International Journal of …, 2016 - search.proquest.com
Data Mining is the most believable approach of the present digital world for analyzing mass
of data sets to obtain unnoticed relationship. The method used for the analysis of statistical …
of data sets to obtain unnoticed relationship. The method used for the analysis of statistical …
Enhanced protein fold prediction method through a novel feature extraction technique
Information of protein 3-dimensional (3D) structures plays an essential role in molecular
biology, cell biology, biomedicine, and drug design. Protein fold prediction is considered as …
biology, cell biology, biomedicine, and drug design. Protein fold prediction is considered as …
Drug side effect prediction through linear neighborhoods and multiple data source integration
W Zhang, Y Chen, S Tu, F Liu… - 2016 IEEE international …, 2016 - ieeexplore.ieee.org
Predicting drug side effects is a critical task in the drug discovery, which attracts great
attentions in both academy and industry. Although lots of machine learning methods have …
attentions in both academy and industry. Although lots of machine learning methods have …
Predict gram-positive and gram-negative subcellular localization via incorporating evolutionary information and physicochemical features into Chou's general PseAAC
In this study, we used structural and evolutionary based features to represent the sequences
of gram-positive and gram-negative subcellular localizations. To do this, we proposed a …
of gram-positive and gram-negative subcellular localizations. To do this, we proposed a …
A unified frame of predicting side effects of drugs by using linear neighborhood similarity
Background Drug side effects are one of main concerns in the drug discovery, which gains
wide attentions. Investigating drug side effects is of great importance, and the computational …
wide attentions. Investigating drug side effects is of great importance, and the computational …
Improving succinylation prediction accuracy by incorporating the secondary structure via helix, strand and coil, and evolutionary information from profile bigrams
Post-translational modification refers to the biological mechanism involved in the enzymatic
modification of proteins after being translated in the ribosome. This mechanism comprises a …
modification of proteins after being translated in the ribosome. This mechanism comprises a …