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 …

Prottrans: Toward understanding the language of life through self-supervised learning

A Elnaggar, M Heinzinger, C Dallago… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Computational biology and bioinformatics provide vast data gold-mines from protein
sequences, ideal for Language Models (LMs) taken from Natural Language Processing …

NetSurfP-3.0: accurate and fast prediction of protein structural features by protein language models and deep learning

MH Høie, EN Kiehl, B Petersen, M Nielsen… - Nucleic acids …, 2022 - academic.oup.com
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 …

Improved protein structure prediction using potentials from deep learning

AW Senior, R Evans, J Jumper, J Kirkpatrick, L Sifre… - Nature, 2020 - nature.com
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 …

Evaluating protein transfer learning with TAPE

R Rao, N Bhattacharya, N Thomas… - Advances in neural …, 2019 - proceedings.neurips.cc
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 …

[HTML][HTML] Modeling aspects of the language of life through transfer-learning protein sequences

M Heinzinger, A Elnaggar, Y Wang, C Dallago… - BMC …, 2019 - Springer
Background Predicting protein function and structure from sequence is one important
challenge for computational biology. For 26 years, most state-of-the-art approaches …

Amino acid encoding methods for protein sequences: a comprehensive review and assessment

X Jing, Q Dong, D Hong, R Lu - IEEE/ACM transactions on …, 2019 - ieeexplore.ieee.org
As the first step of machine-learning based protein structure and function prediction, the
amino acid encoding play a fundamental role in the final success of those methods. Different …

NetSurfP‐2.0: Improved prediction of protein structural features by integrated deep learning

MS Klausen, MC Jespersen, H Nielsen… - Proteins: Structure …, 2019 - Wiley Online Library
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 …

[HTML][HTML] In-silico design of a multi-epitope vaccine candidate against onchocerciasis and related filarial diseases

RA Shey, SM Ghogomu, KK Esoh, ND Nebangwa… - Scientific reports, 2019 - nature.com
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 …

Capturing non-local interactions by long short-term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone …

R Heffernan, Y Yang, K Paliwal, Y Zhou - Bioinformatics, 2017 - academic.oup.com
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 …