Search Results - "Machine Learning and Artificial Intelligence in Bioinformatics"

Modeling aspects of the language of life through transfer-learning protein sequences by Heinzinger, Michael, Elnaggar, Ahmed, Wang, Yu, Dallago, Christian, Nechaev, Dmitrii, Matthes, Florian, Rost, Burkhard

“…Background Predicting protein function and structure from sequence is one important challenge for computational biology. For 26 years, most state-of-the-art…”
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Comprehensive ensemble in QSAR prediction for drug discovery by Kwon, Sunyoung, Bae, Ho, Jo, Jeonghee, Yoon, Sungroh

“…Background Quantitative structure-activity relationship (QSAR) is a computational modeling method for revealing relationships between structural properties of…”
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DPDDI: a deep predictor for drug-drug interactions by Feng, Yue-Hua, Zhang, Shao-Wu, Shi, Jian-Yu

“…Background The treatment of complex diseases by taking multiple drugs becomes increasingly popular. However, drug-drug interactions (DDIs) may give rise to the…”
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Conditional permutation importance revisited by Debeer, Dries, Strobl, Carolin

“…Background Random forest based variable importance measures have become popular tools for assessing the contributions of the predictor variables in a fitted…”
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Novel deep learning model for more accurate prediction of drug-drug interaction effects by Lee, Geonhee, Park, Chihyun, Ahn, Jaegyoon

“…Background Predicting the effect of drug-drug interactions (DDIs) precisely is important for safer and more effective drug co-prescription. Many computational…”
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Graph-based prediction of Protein-protein interactions with attributed signed graph embedding by Yang, Fang, Fan, Kunjie, Song, Dandan, Lin, Huakang

“…Background Protein-protein interactions (PPIs) are central to many biological processes. Considering that the experimental methods for identifying PPIs are…”
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Prediction of heart disease and classifiers’ sensitivity analysis by Almustafa, Khaled Mohamad

“…Background Heart disease (HD) is one of the most common diseases nowadays, and an early diagnosis of such a disease is a crucial task for many health care…”
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ProteinNet: a standardized data set for machine learning of protein structure by AlQuraishi, Mohammed

“…Background Rapid progress in deep learning has spurred its application to bioinformatics problems including protein structure prediction and design. In classic…”
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Malaria parasite detection in thick blood smear microscopic images using modified YOLOV3 and YOLOV4 models by Abdurahman, Fetulhak, Fante, Kinde Anlay, Aliy, Mohammed

“…Background Manual microscopic examination of Leishman/Giemsa stained thin and thick blood smear is still the “gold standard” for malaria diagnosis. One of the…”
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FeatureSelect: a software for feature selection based on machine learning approaches by Masoudi-Sobhanzadeh, Yosef, Motieghader, Habib, Masoudi-Nejad, Ali

“…Background Feature selection, as a preprocessing stage, is a challenging problem in various sciences such as biology, engineering, computer science, and other…”
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A hierarchical integration deep flexible neural forest framework for cancer subtype classification by integrating multi-omics data by Xu, Jing, Wu, Peng, Chen, Yuehui, Meng, Qingfang, Dawood, Hussain, Dawood, Hassan

“…Background Cancer subtype classification attains the great importance for accurate diagnosis and personalized treatment of cancer. Latest developments in…”
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Application of network link prediction in drug discovery by Abbas, Khushnood, Abbasi, Alireza, Dong, Shi, Niu, Ling, Yu, Laihang, Chen, Bolun, Cai, Shi-Min, Hasan, Qambar

“…Background Technological and research advances have produced large volumes of biomedical data. When represented as a network (graph), these data become useful…”
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Improving biomedical named entity recognition with syntactic information by Tian, Yuanhe, Shen, Wang, Song, Yan, Xia, Fei, He, Min, Li, Kenli

“…Background Biomedical named entity recognition (BioNER) is an important task for understanding biomedical texts, which can be challenging due to the lack of…”
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MiPepid: MicroPeptide identification tool using machine learning by Zhu, Mengmeng, Gribskov, Michael

“…Background Micropeptides are small proteins with length < = 100 amino acids. Short open reading frames that could produces micropeptides were traditionally…”
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A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis by Lin, Eugene, Mukherjee, Sudipto, Kannan, Sreeram

“…Background Single-cell RNA sequencing (scRNA-seq) is an emerging technology that can assess the function of an individual cell and cell-to-cell variability at…”
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GAT-LI: a graph attention network based learning and interpreting method for functional brain network classification by Hu, Jinlong, Cao, Lijie, Li, Tenghui, Dong, Shoubin, Li, Ping

“…Background Autism spectrum disorders (ASD) imply a spectrum of symptoms rather than a single phenotype. ASD could affect brain connectivity at different degree…”
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SWnet: a deep learning model for drug response prediction from cancer genomic signatures and compound chemical structures by Zuo, Zhaorui, Wang, Penglei, Chen, Xiaowei, Tian, Li, Ge, Hui, Qian, Dahong

“…Background One of the major challenges in precision medicine is accurate prediction of individual patient’s response to drugs. A great number of computational…”
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A novel collaborative filtering model for LncRNA-disease association prediction based on the Naïve Bayesian classifier by Yu, Jingwen, Xuan, Zhanwei, Feng, Xiang, Zou, Quan, Wang, Lei

“…Background Since the number of known lncRNA-disease associations verified by biological experiments is quite limited, it has been a challenging task to uncover…”
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Keras R-CNN: library for cell detection in biological images using deep neural networks by Hung, Jane, Goodman, Allen, Ravel, Deepali, Lopes, Stefanie C. P., Rangel, Gabriel W., Nery, Odailton A., Malleret, Benoit, Nosten, Francois, Lacerda, Marcus V. G., Ferreira, Marcelo U., Rénia, Laurent, Duraisingh, Manoj T., Costa, Fabio T. M., Marti, Matthias, Carpenter, Anne E.

“…Background A common yet still manual task in basic biology research, high-throughput drug screening and digital pathology is identifying the number, location,…”
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ECFS-DEA: an ensemble classifier-based feature selection for differential expression analysis on expression profiles by Zhao, Xudong, Jiao, Qing, Li, Hangyu, Wu, Yiming, Wang, Hanxu, Huang, Shan, Wang, Guohua

“…Background Various methods for differential expression analysis have been widely used to identify features which best distinguish between different categories…”
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