activity
20202026
most citedA perspective on protein structure prediction using quantum computers

54 citations · 102 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2026

Quantum Kernel Estimation for the Discovery of Early Lung Cancer Detection

Hamed Javidi, Alex Zajichek, Hakan Doga +3

Lung cancer screening with low-dose chest computed tomography reduces mortality, but its impact is limited by uptake, adherence, and management challenges. Blood-based cell-free DN…

quant-ph2026

Protein folding on a 64 qubit trapped-ion hardware via counterdiabatic quantum optimization

Alejandro Gomez Cadavid, Pavle Nikačević, Pranav Chandarana +11

We report the largest trapped-ion hardware demonstration of lattice protein-folding optimization to date, using bias-field digitized counterdiabatic quantum optimization (BF-DCQO)…

quant-ph2026

Molecular Quantum Computations on a Protein

Akhil Shajan, Danil Kaliakin, Fangchun Liang +7

This work presents the implementation of a fragment-based, quantum-centric supercomputing workflow for computing molecular electronic structure using quantum hardware. The workflow…

quant-ph2025

Quantum Algorithm for Protein Structure Prediction Using the Face-Centered Cubic Lattice

Rui-Hao Li, Hakan Doga, Bryan Raubenolt +16

In this work, we present the first implementation of the face-centered cubic (FCC) lattice model for protein structure prediction with a quantum algorithm. Our motivation to encode…

q-bio.QM2025★ 4 cited

Towards Quantum Tensor Decomposition in Biomedical Applications

Myson Burch, Jiasen Zhang, Gideon Idumah +12

Tensor decomposition has emerged as a powerful framework for feature extraction in multi-modal biomedical data. In this review, we present a comprehensive analysis of tensor decomp…

quant-ph2024★ 35 cited

Towards quantum computing for clinical trial design and optimization: A perspective on new opportunities and challenges

Hakan Doga, M. Emre Sahin, Joao Bettencourt-Silva +10

Clinical trials are pivotal in the drug discovery process to determine the safety and efficacy of a drug candidate. The high failure rates of these trials are attributed to deficie…

quant-ph2023★ 54 cited

A perspective on protein structure prediction using quantum computers

Hakan Doga, Bryan Raubenolt, Fabio Cumbo +5

Despite the recent advancements by deep learning methods such as AlphaFold2, \textit{in silico} protein structure prediction remains a challenging problem in biomedical research. W…

quant-ph2023★ 9 cited

Towards quantum-enabled cell-centric therapeutics

Saugata Basu, Jannis Born, Aritra Bose +30

In recent years, there has been tremendous progress in the development of quantum computing hardware, algorithms and services leading to the expectation that in the near future qua…

math.GT2020

A Combinatorial Description of the Knot Concordance Invariant Epsilon

Subhankar Dey, Hakan Doga

In this paper, we give a combinatorial description of the concordance invariant defined by Hom in \cite{hom2011knot}, prove some properties of this invariant using gr…