9 papers · ranked by Valyu relevance
Ghanshyam Chandra, Md Helal Hossen, Stephan Scholz, Alexander T Dilthey + 2 more
Affordable genotyping methods are essential in genomics. Commonly used genotyping methods primarily support single nucleotide variants and short indels but neglect structural variants. Additionally, accuracy of read alignments to a reference genome is unreliable in highly polymorphic and repetitive regions, further…
Xinyu Gu, Stefan Ivanovic, Daniel W. Feng, Mohammed El-Kebir
Summarizing a collection P of related RNA secondary structures is a key challenge in applications like evolutionary analysis, alternative fold studies and mRNA vaccine design. This requires both clustering the input structures into similar groups and identifying the core structural motifs on which they agree or differ.…
Mengzhen Guo, Stefan Grünewald
We present Lpnet, a variant of the widely used Neighbor-net method that approximates pairwise distances between taxa by a circular phylogenetic network. We first apply standard methods to construct a binary phylogenetic tree and then use integer linear programming to compute an optimal circular orderings that agrees…
Theo Knijnenburg, Gunnar Klau, Francesco Iorio, Mathew Garnett + 3 more
Mining large datasets using machine learning approaches often leads to models that are hard to interpret and not amenable to the generation of hypotheses that can be experimentally tested. Finding ‘actionable knowledge’ is becoming more important, but also more challenging as datasets grow in size and complexity. We…
Shouyong Jiang, Yong Wang, Marcus Kaiser, Natalio Krasnogor
Flux balance analysis (FBA) based bilevel optimisation has been a great success in redesigning metabolic networks for biochemical overproduction. To date, many computational approaches have been developed to solve the resulting bilevel optimisation problems. However, most of them are of limited use due to biased…
Authors not listed
Experimental design plays an important role in efficiently acquiring informative data for system characterization and deriving robust conclusions under resource limitations. Recent advancements in high-throughput experimentation coupled with machine learning have notably improved experimental procedures. While Bayesian…
Liwei Cao, Danilo Russo, Vassilios S. Vassiliadis, Alexei Lapkin
A mixed-integer nonlinear programming (MINLP) formulation for symbolic regression was proposed to identify physical models from noisy experimental data. The formulation was tested using numerical models and was found to be more efficient than the previous literature example with respect to the number of predictor…
Authors not listed
Automated chemistry platforms hold the potential to enable large-scale organic synthesis campaigns, such as producing a library of compounds for biological evaluation. The efficiency of such platforms will depend on the schedule according to which the synthesis operations are executed. In this work, we study the…
Eugene Christo V R, Christoph Robert Meinecke, Bert Nitzsche, Roman Lyttleton + 5 more
Network-based biocomputing (NBC) presents an energy-efficient, parallel computing approach for solving nondeterministic polynomial time (NP) complete problems by leveraging motor-driven cytoskeletal filaments that explore all possible solutions through nanofabricated networks in a massively parallel fashion. However…