A brief history of bioinformatics
J Gauthier, AT Vincent, SJ Charette… - Briefings in …, 2019 - academic.oup.com
It is easy for today's students and researchers to believe that modern bioinformatics
emerged recently to assist next-generation sequencing data analysis. However, the very …
emerged recently to assist next-generation sequencing data analysis. However, the very …
Prottrans: Toward understanding the language of life through self-supervised learning
Computational biology and bioinformatics provide vast data gold-mines from protein
sequences, ideal for Language Models (LMs) taken from Natural Language Processing …
sequences, ideal for Language Models (LMs) taken from Natural Language Processing …
[HTML][HTML] Improved protein structure prediction using potentials from deep learning
Protein structure prediction can be used to determine the three-dimensional shape of a
protein from its amino acid sequence. This problem is of fundamental importance as the …
protein from its amino acid sequence. This problem is of fundamental importance as the …
NetSurfP-3.0: accurate and fast prediction of protein structural features by protein language models and deep learning
Recent advances in machine learning and natural language processing have made it
possible to profoundly advance our ability to accurately predict protein structures and their …
possible to profoundly advance our ability to accurately predict protein structures and their …
Evaluating protein transfer learning with TAPE
Protein modeling is an increasingly popular area of machine learning research. Semi-
supervised learning has emerged as an important paradigm in protein modeling due to the …
supervised learning has emerged as an important paradigm in protein modeling due to the …
[HTML][HTML] Modeling aspects of the language of life through transfer-learning protein sequences
M Heinzinger, A Elnaggar… - BMC …, 2019 - bmcbioinformatics.biomedcentral …
Predicting protein function and structure from sequence is one important challenge for
computational biology. For 26 years, most state-of-the-art approaches combined machine …
computational biology. For 26 years, most state-of-the-art approaches combined machine …
NetSurfP‐2.0: Improved prediction of protein structural features by integrated deep learning
The ability to predict local structural features of a protein from the primary sequence is of
paramount importance for unraveling its function in absence of experimental structural …
paramount importance for unraveling its function in absence of experimental structural …
Deep learning for mining protein data
The recent emergence of deep learning to characterize complex patterns of protein big data
reveals its potential to address the classic challenges in the field of protein data mining …
reveals its potential to address the classic challenges in the field of protein data mining …
[HTML][HTML] In-silico design of a multi-epitope vaccine candidate against onchocerciasis and related filarial diseases
Onchocerciasis is a parasitic disease with high socio-economic burden particularly in sub-
Saharan Africa. The elimination plan for this disease has faced numerous challenges. A …
Saharan Africa. The elimination plan for this disease has faced numerous challenges. A …
Capturing non-local interactions by long short-term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone …
Motivation The accuracy of predicting protein local and global structural properties such as
secondary structure and solvent accessible surface area has been stagnant for many years …
secondary structure and solvent accessible surface area has been stagnant for many years …