DrugE-Rank: Predicting Drug-Target Interactions by Learning to Rank

Identifying drug-target interactions is crucial for the success of drug discovery. Approaches based on machine learning for this problem can be divided into two types: feature-based and similarity-based methods. By utilizing the “Learning to rank” framework, we propose a new method, DrugE-Rank, to combine these two different types of methods for improving the prediction performance of new candidate drugs and targets. DrugE-Rank is available at http://datamining-iip.fudan.edu.cn/service/DrugE-Rank/

Étude expérimentale des interactions entre deux particules sphériques, relâchées dans l’eau stagnante

L’interaction entre des particules submergées dans l’eau, un liquide que nous utilisons dans notre vie quotidienne, est un sujet de recherche intéressant, qui a été abordé dans plusieurs domaines – génie chimique, génie industriel, génie énergétique, etc. Dans ce mémoire, nous sommes intéressés et nous nous concentrons sur les interactions entre deux particules sphériques identiques. Les objectifs sont constitués de deux parties : ce qui est spécifique pour ce projet, contribuer à l’élaboration d’un outil de prédiction des trajectoires de deux particules sphériques, rigides, identiques, initialement immobiles, qui sont submergées ; et à long terme, construire un modèle permettant de prédire la trajectoire d’une particule ou d’une bulle dans l’eau, au sein d’un nuage d’autres particules ou bulles. Ce projet de recherche commence par la conception et la construction du tout nouveau dispositif expérimental, dans lequel une pompe à vide a été utilisée afin de compléter le mécanisme de fixation et de libération de deux particules. Les expériences sont faites en utilisant plusieurs types de particules (de différentes tailles, de 3.175 mm à 9.525 mm, et de différentes masses volumiques, de 670 kg/m3 à 1410 kg/m3, dont la plage est approximativement autour de celle de l’eau) et des résultats similaires (les trajectoires, les évolutions des vitesses, etc.) sont obtenus. Pour chaque paire de particules qui sont initialement côte à côte sans vitesse initiale, elles commencent par s’approcher et puis s’éloignent, en accélérant (en montant ou en descendant), mais en restant dans un même plan vertical peu après la libération ; pour chaque paire de particules qui sont initialement devant derrière sans vitesse initiale, elles s’approchent légèrement puis celle qui est derrière accélère d’une façon telle que la ligne reliant leurs centres devient au fur et à mesure horizontale (transversale). À la fin, une discussion sur l’ensemble des résultats est proposée. Un bilan de tout ce que j’ai pu faire et tout ce que je n’ai pas fait, des améliorations et des travaux futurs sont discutés et présentés, pour que ce projet puisse aller plus loin dans le futur, avant d’atteindre son objectif final.----------Abstract The interaction between particles submerged in water, a liquid that we use in our daily life, is an interesting research topic, which has been addressed in several fields - chemical engineering, industrial engineering, energy engineering, etc. In this thesis, we are interested and we focus on the one between two spherical particles, which are identical. The objectives consist of two parts: what is specific for this project, contributing to the development of a tool for predicting the trajectories of two spherical, rigid, identical, initially immobile particles which are submerged; and in the long term, build a model able to predict the trajectory of a particle or a bubble in water, within a cloud of other particles or bubbles. This research project begins with the design and construction of the brand new experimental device, in which a vacuum pump was used to complete the mechanism of attachment and release of two particles. The experiments are done using several types of particles (of di˙erent sizes, from 3.175 mm to 9.525 mm, and di˙erent densities, from 670 kg/m3 to 1410 kg/m3, of which the range is around that of the water) and similar results (the trajectories, the evolutions of the speeds, etc.) are obtained. Basically, for each pair of particles that are initially side to side with no initial velocity, they start by approaching and then move away, while accelerating and going up or going down, but staying in the same vertical plane shortly after the liberation ; for each pair of particles that are initially in a vertical line without initial velocity, they approach slightly and then the one behind accelerates in such a way that the line connecting their centers gradually becomes horizontal (transverse). At the end we discuss the experimental results. A review of all that I have been able to do and all that I have not done, improvements and future work are discussed and presented, so that this project can go further in the future, before reaching its final goal

Tenovin 3 induces apoptosis and ferroptosis in EGFR 19del non small cell lung cancer cells

Abstract Epidermal growth factor receptor (EGFR) exon 19 deletion is a major driver for the drug resistance of non-small cell lung cancer (NSCLC). Identification small inhibitor capable of selectively inhibiting EGFR-19del NSCLC is a desirable strategy to overcome drug resistance in NSCLC. This study aims to screen an inhibitor for EGFR exon 19 deletion cells and explore its underlying mechanism. High through-put screen was conducted to identify an inhibitor for EGFR-19del NSCLC cells. And tenovin-3 was identified as a selective inhibitor of PC9 cells, an EGFR-19del NSCLC cells. Tenovin-3 showed particular inhibition effect on PC9 cells proliferation through inducing apoptosis and ferroptosis. Mechanistically, tenovin-3 might induce the apoptosis and ferroptosis of PC9 cells through mitochondrial pathway, as indicated by the change of VDAC1 and cytochrome c (cyt c). And bioinformatics analyses showed that the expression levels of SLC7A11 and CPX4 were correlated with NSCLC patient’s survival. Our findings provide evidences for tenovin-3 to be developed into a novel candidate agent for NSCLC with EGFR exon 19 deletion. Our study also suggests that inducing ferroptosis may be a therapeutic strategy for NSCLC with EGFR exon 19 deletion

Chromosome-scale assembly and whole-genome sequencing of 266 giant panda roundworms provide insights into their evolution, adaptation and potential drug targets

Helminth diseases have long been a threat to the health of humans and animals. Roundworms are important organisms for studying parasitic mechanisms, disease transmission and prevention. The study of parasites in the giant panda is of importance for understanding how roundworms adapt to the host. Here, we report a high‐quality chromosome‐scale genome of Baylisascaris schroederi with a genome size of 253.60 Mb and 19,262 predicted protein‐coding genes. We found that gene families related to epidermal chitin synthesis and environmental information processes in the roundworm genome have expanded significantly. Furthermore, we demonstrated unique genes involved in essential amino acid metabolism in the B. schroederi genome, inferred to be essential for the adaptation to the giant panda‐specific diet. In addition, under different deworming pressures, we found that four resistance‐related genes (glc‐1, nrf‐6, bre‐4 and ced‐7) were under strong positive selection in a captive population. Finally, 23 known drug targets and 47 potential drug target proteins were identified. The genome provides a unique reference for inferring the early evolution of roundworms and their adaptation to the host. Population genetic analysis and drug sensitivity prediction provide insights revealing the impact of deworming history on population genetic structure of importance for disease prevention

Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease.

Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance

Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease

Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance