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51 gevonden resultaten

nr	titel	auteur	tijdschrift	jaar	jaarg.	afl.	pagina('s)	type
1	A bibliometric analysis of the Cheminformatics/QSAR literature (2000–2023) for predictive modeling in data science using the SCOPUS database	Banerjee, Arkaprava			29	4	p. 3703-3715	artikel
2	A 4D tensor-enhanced multi-dimensional convolutional neural network for accurate prediction of protein–ligand binding affinity	Huang, Dingfang			29	4	p. 3041-3058	artikel
3	Advancing antimalarial drug discovery: ensemble machine learning models for predicting PfPK6 inhibitor activity	Gholami, Maryam			29	4	p. 3575-3586	artikel
4	AI and ML for small molecule drug discovery in the big data era III	Roy, Kunal			29	4	p. 2863	artikel
5	AI-DPAPT: a machine learning framework for predicting PROTAC activity	Abouzied, Amr S.			29	4	p. 2995-3007	artikel
6	A multiscale molecular structural neural network for molecular property prediction	Shi, Zhiwei			29	4	p. 3273-3292	artikel
7	A multitask interpretable model with graph attention mechanism for activity prediction of low-data PIM inhibitors	Wang, Zixiao			29	4	p. 3101-3112	artikel
8	ASS1 is a hub gene and possible therapeutic target for regulating metabolic dysfunction-associated steatotic liver disease modulated by a carbohydrate-restricted diet	Chen, Shaojun			29	4	p. 3717-3732	artikel
9	Cangrelor and AVN-944 as repurposable candidate drugs for hMPV: analysis entailed by AI-driven in silico approach	Thaikkad, Amritha			29	4	p. 3587-3605	artikel
10	Classification models and SAR analysis of anaplastic lymphoma kinase (ALK) inhibitors using machine learning algorithms with two data division methods	Qu, Dan			29	4	p. 2919-2943	artikel
11	Computational screening of umami tastants using deep learning	Dutta, Prantar			29	4	p. 2979-2993	artikel
12	Correction: Machine learning-based activity prediction of phenoxy-imine catalysts and its structure–activity relationship study	Zhou, Xiaoke			29	4	p. 3423	artikel
13	Deep learning in the discovery of antiviral peptides and peptidomimetics: databases and prediction tools	Nawaz, Maryam			29	4	p. 3753-3788	artikel
14	Discovery of novel potential 11β-HSD1 inhibitors through combining deep learning, molecular modeling, and bio-evaluation	Chen, Xiaodie			29	4	p. 3485-3500	artikel
15	Drug repurposing to identify potential FDA-approved drugs targeting three main angiogenesis receptors through a deep learning framework	Torabi, Mohammadreza			29	4	p. 3637-3659	artikel
16	Dual inhibition of AChE and MAO-B in Alzheimer’s disease: machine learning approaches and model interpretations	Hou, Qinghe			29	4	p. 3113-3130	artikel
17	Enhancing PI3Kγ inhibitor discovery: a machine learning-based virtual screening approach integrating pharmacophores, docking, and molecular descriptors	Jia, Lei			29	4	p. 3661-3678	artikel
18	Explainable AI-driven prediction of APE1 inhibitors: enhancing cancer therapy with machine learning models and feature importance analysis	Iqbal, Aga Basit			29	4	p. 3371-3390	artikel
19	First report on analysis of chemical space, scaffold diversity, critical structural features of HDAC11 inhibitors	Bhagat, Rinki Prasad			29	4	p. 3679-3702	artikel
20	General structure-activity relationship models for the inhibitors of Adenosine receptors: A machine learning approach	Janbozorgi, M.			29	4	p. 3253-3272	artikel
21	Generative adversarial network (GAN) model-based design of potent SARS-CoV-2 Mpro inhibitors using the electron density of ligands and 3D binding pockets: insights from molecular docking, dynamics simulation, and MM-GBSA analysis	Chakraborty, Annesha			29	4	p. 3059-3075	artikel
22	GraphkmerDTA: integrating local sequence patterns and topological information for drug-target binding affinity prediction and applications in multi-target anti-Alzheimer’s drug discovery	Zhang, Zuolong			29	4	p. 3147-3164	artikel
23	HDAC3_VS_assistant: cheminformatics-driven discovery of histone deacetylase 3 inhibitors	Tinkov, Oleg V.			29	4	p. 3165-3187	artikel
24	iDCNNPred: an interpretable deep learning model for virtual screening and identification of PI3Ka inhibitors against triple-negative breast cancer	Jaiswal, Ravishankar			29	4	p. 3077-3100	artikel
25	Identification and validation of oxidative stress-related diagnostic markers for recurrent pregnancy loss: insights from machine learning and molecular analysis	Hu, Hui			29	4	p. 2881-2897	artikel
26	Identification of STAT3 phosphorylation inhibitors using generative deep learning, virtual screening, molecular dynamics simulations, and biological evaluation for non-small cell lung cancer therapy	Cai, Weiji			29	4	p. 3189-3205	artikel
27	Identify critical genes of breast cancer and corresponding leading natural product compounds of potential therapeutic targets	Fan, Xiaokai			29	4	p. 3009-3022	artikel
28	Integrated AI and machine learning pipeline identifies novel WEE1 kinase inhibitors for targeted cancer therapy	Chandrasekaran, Jaikanth			29	4	p. 3425-3448	artikel
29	Integrated machine learning-based virtual screening and biological evaluation for identification of potential inhibitors against cathepsin K	Parwez, Shahid			29	4	p. 2865-2880	artikel
30	Integrating deep learning and molecular dynamics simulations for FXR antagonist discovery	Yang, Yueying			29	4	p. 3391-3409	artikel
31	Integrating machine learning and structural dynamics to explore B-cell lymphoma-2 inhibitors for chronic lymphocytic leukemia therapy	Bharadwaj, Rima			29	4	p. 3233-3252	artikel
32	Integrating traditional QSAR and read-across-based regression models for predicting potential anti-leishmanial azole compounds	Nandi, Rajat			29	4	p. 3207-3231	artikel
33	Interpretable drug-target affinity prediction based on pre-trained models’ output as embeddings and based on structure-aware cross-attention for feature fusion	Zheng, Fang			29	4	p. 3537-3554	artikel
34	Leveraging machine learning to predict drug permeation: impact of menthol and limonene as enhancers	Yadav, Manisha			29	4	p. 3131-3146	artikel
35	Machine learning and cheminformatics-based Identification of lichen-derived compounds targeting mutant PBP4R200L in Staphylococcus aureus	Mathpal, Shalini			29	4	p. 3345-3370	artikel
36	Machine learning approaches for predicting the small molecule–miRNA associations: a comprehensive review	Panghalia, Ashish			29	4	p. 3825-3856	artikel
37	Machine learning-based activity prediction of phenoxy-imine catalysts and its structure–activity relationship study	Zhou, Xiaoke			29	4	p. 3411-3422	artikel
38	Machine learning-based screening and molecular simulations for discovering novel PARP-1 inhibitors targeting DNA repair mechanisms for breast cancer therapy	Shahab, Muhammad			29	4	p. 3323-3343	artikel
39	Machine learning models to identify lead compound and substitution optimization to have derived energetics and conformational stability through docking and MD simulations for sphingosine kinase 1	Dhanabalan, Anantha Krishnan			29	4	p. 2945-2977	artikel
40	Machine learning, network pharmacology, and molecular dynamics reveal potent cyclopeptide inhibitors against dengue virus proteins	Imam, Mohammed A.			29	4	p. 2899-2917	artikel
41	Machine learning: Python tools for studying biomolecules and drug design	Ryzhkov, Fedor V.			29	4	p. 3789-3824	artikel
42	MedKG: enabling drug discovery through a unified biomedical knowledge graph	Kumari, Madhavi			29	4	p. 3465-3483	artikel
43	Optimizing kinase and PARP inhibitor combinations through machine learning and in silico approaches for targeted brain cancer therapy	Poustforoosh, Alireza			29	4	p. 3293-3303	artikel
44	PPARγ modulator predictor (PGMP_v1): chemical space exploration and computational insights for enhanced type 2 diabetes mellitus management	Amin, Sk. Abdul			29	4	p. 3305-3321	artikel
45	Probing the dark chemical matter against PDE4 for the management of psoriasis using in silico, in vitro and in vivo approach	Swapna, B.			29	4	p. 3449-3464	artikel
46	Python tools for structural tasks in chemistry	Ryzhkov, Fedor V.			29	4	p. 3733-3752	artikel
47	QMGBP-DL: a deep learning and machine learning approach for quantum molecular graph band-gap prediction	Abbassi, Outhman			29	4	p. 3501-3515	artikel
48	“Several birds with one stone”: exploring the potential of AI methods for multi-target drug design	Mukaidaisi, Muhetaer			29	4	p. 3023-3039	artikel
49	Targeting Poly (ADP-ribose) polymerase-1 (PARP-1) for DNA repair mechanism through QSAR-based virtual screening and MD simulation	Cao, Kun			29	4	p. 3517-3535	artikel
50	Titania: an integrated tool for in silico molecular property prediction and NAM-based modeling	Koutroumpa, Nikoletta-Maria			29	4	p. 3555-3573	artikel
51	Unraveling potent Glycyrrhiza glabra flavonoids as AKT1 inhibitors using network pharmacology and machine learning-assisted QSAR	Niharika, Desu Gayathri			29	4	p. 3607-3635	artikel

51 gevonden resultaten

Koninklijke Bibliotheek - Nationale Bibliotheek van Nederland