71 citations · 137 across the 8 of their papers we have counts for
5 papers · 1 filter
Ankh3: Multi-Task Pretraining with Sequence Denoising and Completion Enhances Protein Representations
Hazem Alsamkary, Mohamed Elshaffei, Mohamed Elkerdawy +1
Protein language models (PLMs) have emerged as powerful tools to detect complex patterns of protein sequences. However, the capability of PLMs to fully capture information on prote…
Beyond Simple Concatenation: Fairly Assessing PLM Architectures for Multi-Chain Protein-Protein Interactions Prediction
Hazem Alsamkary, Mohamed Elshaffei, Mohamed Soudy +5
Protein-protein interactions (PPIs) are fundamental to numerous cellular processes, and their characterization is vital for understanding disease mechanisms and guiding drug discov…
Ankh: Optimized Protein Language Model Unlocks General-Purpose Modelling
Ahmed Elnaggar, Hazem Essam, Wafaa Salah-Eldin +4
As opposed to scaling-up protein language models (PLMs), we seek improving performance via protein-specific optimization. Although the proportionality between the language model si…
ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance Computing
Ahmed Elnaggar, Michael Heinzinger, Christian Dallago +9
Computational biology and bioinformatics provide vast data gold-mines from protein sequences, ideal for Language Models taken from NLP. These LMs reach for new prediction frontiers…
Named-Entity Linking Using Deep Learning For Legal Documents: A Transfer Learning Approach
Ahmed Elnaggar, Robin Otto, Florian Matthes
In the legal domain it is important to differentiate between words in general, and afterwards to link the occurrences of the same entities. The topic to solve these challenges is c…