24 papers · ranked by Valyu relevance
Authors not listed
Fragment-based drug design (FBDD) has become a key approach in structure-based drug discovery, allowing researchers to systematically develop molecular fragments into potent ligands. Although recent generative AI models, such as diffusion-based approaches, show great potential for designing new molecules, applying them…
Jiaxin Jiang, Yunxiang Zhao, Lyu Xu, Byron Choi + 3 more
—Transaction flow networks are crucial in detecting illicit activities such as wash trading, credit card fraud, cashback arbitrage fraud, and money laundering. Our collaborator, Grab, a leader in digital payments in Southeast Asia, faces increasingly sophisticated fraud patterns in its transaction flow networks. In…
Hugo Magalhães, Jonas Weber, Gunnar W. Klau, Tobias Marschall + 1 more
Variation of sequence copy number (CN) between individuals can be associated with phenotypical differences. Consequently, CN calling is an important step for disease association and identification, as well as for genome assembly validation. Traditionally, CN calling is done by mapping sequencing reads to a linear…
Shruthi Kannappan, Ashwina Kumar, Rupesh Nasre
MaxFlow is a fundamental problem in graph theory and combinatorial optimisation, used to determine the maximum flow from a source node to a sink node in a flow network. It finds applications in diverse domains, including computer networks, transportation, and image segmentation. The core idea is to maximise the total…
Shridharan Chandramouli
| 1 | | Introduction | | | |---|-----------------------------------------------------|---------------------------------------------------------------------------|----|--| | | 1.1 | Motivation | 1 | | | | 1.2 | Proper Order Multi-Column Graph Structure | 2 | | | | 1.3 | General Maxflow/Mincut Problem Definition | 2 | |…
Ke Chen, Abhishek Talesara, Sanchal Thakkar, Mingfu Shao
The minimum flow decomposition problem abstracts a set of key tasks in bioinformatics, including metagenome and transcriptome assembly. These tasks, collectively known as multi-assembly, aim to reconstruct multiple genomic sequences from reads obtained from mixed samples. The reads are first organized into a directed…
Shruthi Kannappan, Ashwina Kumar, Rupesh Nasre
The Maximum Flow (Max-Flow) problem is a cornerstone in graph theory and combinatorial optimization, aiming to determine the largest possible flow from a designated source node to a sink node within a capacitated flow network. It has extensive applications across diverse domains such as computer networking…
Faisal Saleem, Alicja Wiora, Józef Wiora
Regulated flow systems exhibit a variable dynamic behavior when subjected to distinct inputs. The significant non-linear behavior of the system at low inputs and the difference in the output pattern for the increase and decrease in flow pose challenges in modeling. One way is to identify separate sets of parameters for…
Eleanor Wiesler, Trace Baxley
We propose a learning-augmented framework for accelerating max-flow computation and image segmentation by integrating Graph Neural Networks (GNNs) with the Ford-Fulkerson algorithm. Rather than predicting initial flows, our method learns edge importance probabilities to guide augmenting path selection. We introduce a…
Ke Chen, Abhishek Talesara, Sanchal Thakkar, Mingfu Shao
The minimum flow decomposition problem abstracts a set of key tasks in bioinformatics, including metagenome and transcriptome assembly. These tasks, collectively known as multi-assembly, aim to reconstruct multiple genomic sequences from reads obtained from mixed samples. The reads are first organized into a directed…
Sebastiano Montante, Daniel Yokosawa, Leon Li, Alexander Butyaev + 17 more
Manual flow cytometry gating requires up to one hour per sample with 32% inter-expert variability, creating critical bottlenecks in immunological research reproducibility. To address this, we developed flowMagic, a machine learning algorithm for automated gating that is trained on both expert-curated data (template…
Authors not listed
Transition state (TS) geometries of chemical reactions are key to understanding reaction mechanisms and estimating kinetic properties. Inferring these directly from 2D reaction graphs offers chemists a powerful tool for rapid and accessible reaction analysis. Quantum chemical methods for computing TSs are…
Adam Siepel, Rebecca Hassett, Stephen J. Staklinski
Bayesian phylogenetic inference is now widely used but remains heavily reliant on Markov chain Monte Carlo (MCMC) sampling, which is computationally intensive and requires careful convergence monitoring. Variational inference (VI) is an appealing alternative that approximates posterior distributions without sampling…
Mehmet Tugrul Birtek, Vural Aktas, Bora Aktas, Ahmed Choukri Abdullah + 2 more
Microfluidics enable high-precision and cost-effective processing of biological and chemical substances. However, designing and fabricating microfluidic chips typically requires substantial expertise and numerous design iterations, posing considerable barriers to entry for nonexperts. We introduce μFluidicGenius (μFG)…
Fernando H. C. Dias, Lucia Williams, Brendan Mumey, Alexandru I. Tomescu
Minimum flow decomposition (MFD) - the problem of finding a minimum set of weighted source-to-sink paths that perfectly decomposes a flow - is a classical problem in Computer Science, and variants of it are powerful models in a different fields such as Bioinformatics and Transportation. Even on acyclic graphs, the…
Authors not listed
Self-driving laboratories (SDLs) promise accelerated scientific discovery and product development by closing the loop between robotic execution and AI/ML-driven decision making. In practice, however, SDL orchestration remains fragmented; workflows are typically encoded as laboratory-specific scripts or bespoke…
Chuandong Chen, Dishi Lin, Qinghai Liu, Zhifeng Lin
Redistribution layer ordered routing is a critical problem in fan-out wafer-level chip-scale packaging (WLCSP) design. The traditional integer linear programming (ILP) method is inefficient in dealing with the ordered routing problem of multiple-capacity. Hence, we propose a high-performance ordered routing algorithm…
Xi Wang, Aonan He, Chunfeng Yang, Jingjing Li + 3 more
Traveling waves of neural activity are fundamental to cortical function, yet their spatiotemporal dynamics and structural constraints remain less understood in human brain. Conventional analyses focus on network topology and spatial geometry of neural signals, with limited emphasis on wave dynamics at high…
Patthadon Tantiameorn, Grittin Nuntasombat, Jittat Fakcharoenphol
Sketch data structures are very useful for computing statistics on streaming data, including network traffic, server requests, and financial transactions. In recent work, FermatSketch was introduced as an underlying data structure used to monitor changes in network states. It is a linear data structure that maintains…
Joan Marcè i Igual, Marc Geilen, Mitra Nasri, Twan Basten
Optimising productivity of tightly coupled production lines in, for instance, the production printing or semiconductor industry is difficult due to the diversity of products resulting in different product flows, the variety of constraints, and the precise timing required to coordinate multiple tightly coupled machines.…
Authors not listed
Azo dyes constitute one of the largest and most commercially important classes of synthetic colorants, widely applied in textiles, plastics, inks, and food. However, their manufacture through traditional batch processes is often constrained by safe-ty risks, poor heat and mass transfer, and inconsistent product…
Authors not listed
Solubility is the maximum amount of solutes that can dissolve in a certain amount of solvent at a certain temperature, and it is significant in battery electrolyte research since it confines the design space. Thus, solubility measurement is a critical constraint on running self-driving labs for battery electrolyte…
Authors not listed
This article presents an overview about the state of the art in the development of structured packings for distillation applications. The focus is on highlighting different approaches including heuristic development cycles, the development of new packing structures, 3D-printing as tool for manufacturing, and…
Jing Xie, Qi Duan
Biological pathway analysis often requires identifying interventions that block reachability to an undesirable state, such as a disease-associated module, toxic byproduct, or adverse phenotype, while preserving reachability among essential biological functions. Motivated by this setting, we study the Reachability…