日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

DeepMolecules: a web server for predicting enzyme and transporter-small molecule interactions

DeepMolecules:一个用于预测酶和转运蛋白与小分子相互作用的Web服务器

Kroll, Alexander; Rousset, Yvan; Spitzlei, Thomas; Lercher, Martin J

Horizontal Gene Transfer Inference: Gene Presence-Absence Outperforms Gene Trees

水平基因转移推断:基因存在与否优于基因树

Mishra, Swastik; Lercher, Martin J

SPOT: A machine learning model that predicts specific substrates for transport proteins

SPOT:一种预测转运蛋白特定底物的机器学习模型

Kroll, Alexander; Niebuhr, Nico; Butler, Gregory; Lercher, Martin J

A multimodal Transformer Network for protein-small molecule interactions enhances predictions of kinase inhibition and enzyme-substrate relationships

用于蛋白质-小分子相互作用的多模态Transformer网络增强了对激酶抑制和酶-底物关系的预测。

Kroll, Alexander; Ranjan, Sahasra; Lercher, Martin J

DLKcat cannot predict meaningful k (cat) values for mutants and unfamiliar enzymes

DLKcat 无法预测突变体和未知酶的有意义的 k(cat) 值。

Kroll, Alexander; Lercher, Martin J

A general model to predict small molecule substrates of enzymes based on machine and deep learning

基于机器学习和深度学习的酶小分子底物预测通用模型

Kroll, Alexander; Ranjan, Sahasra; Engqvist, Martin K M; Lercher, Martin J

Turnover number predictions for kinetically uncharacterized enzymes using machine and deep learning

利用机器学习和深度学习预测动力学未表征酶的周转数

Kroll, Alexander; Rousset, Yvan; Hu, Xiao-Pan; Liebrand, Nina A; Lercher, Martin J

Proteome efficiency of metabolic pathways in Escherichia coli increases along the nutrient flow

大肠杆菌代谢途径的蛋白质组效率随营养流的增加而提高

Hu, Xiao-Pan; Schroeder, Stefan; Lercher, Martin J

Mathematical properties of optimal fluxes in cellular reaction networks at balanced growth

平衡生长状态下细胞反应网络中最优通量的数学特性

Dourado, Hugo; Liebermeister, Wolfram; Ebenhöh, Oliver; Lercher, Martin J

Optimal density of bacterial cells

细菌细胞的最佳密度

Pang, Tin Yau; Lercher, Martin J