| 1. |
- Barros, M, et al.
(författare)
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Feed-forward and feedback control in astrocytes for Ca2+-based molecular communications nanonetworks
- 2018
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Ingår i: IEEE/ACM Transactions on Computational Biology & Bioinformatics. - 1545-5963 .- 1557-9964.
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Tidskriftsartikel (refereegranskat)abstract
- Synaptic plasticity depends on the gliotransmitters' concentration in the synaptic channel. And, an abnormal concentration of gliotransmitters is linked to neurodegenerative diseases, including Alzheimer's, Parkinson's, and epilepsy. In this paper, a theoretical investigation of the cause of the abnormal concentration of gliotransmitters and how to achieve its control is presented through a Ca2+-signalling-based molecular communications framework. A feed-forward and feedback control technique is used to manipulate IP3 values to stabilise the concentration of Ca2+ inside the astrocytes. The theoretical analysis of the given model aims i) to stabilize the Ca2+ concentration around a particular desired level in order to prevent abnormal gliotransmitters' concentration (extremely high or low concentration can result in neurodegeneration), ii) to improve the molecular communication performance that utilises Ca2+ signalling, and maintain gliotransmitters' regulation remotely. It shows that the refractory periods from Ca2+ can be maintained to lower the noise propagation resulting in smaller time-slots for bit transmission, which can also improve the delay and gain performances. The proposed approach can potentially lead to novel nanomedicine solutions for the treatment of neurodegenerative diseases, where a combination of nanotechnology and gene therapy approaches can be used to elicit the regulated Ca2+ signalling in astrocytes, ultimately improving neuronal activity.
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| 2. |
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| 3. |
- Cáceres, Manuel, et al.
(författare)
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Safety in Multi-Assembly via Paths Appearing in All Path Covers of a DAG
- 2022
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Ingår i: IEEE/ACM Transactions on Computational Biology & Bioinformatics. - : Institute of Electrical and Electronics Engineers (IEEE). - 1545-5963 .- 1557-9964 .- 2374-0043. ; 19:6, s. 3673-3684
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Tidskriftsartikel (refereegranskat)abstract
- A multi-assembly problem asks to reconstruct multiple genomic sequences from mixed reads sequenced from all of them. Standard formulations of such problems model a solution as a path cover in a directed acyclic graph, namely a set of paths that together cover all vertices of the graph. Since multi-assembly problems admit multiple solutions in practice, we consider an approach commonly used in standard genome assembly: output only partial solutions ( contigs , or safe paths ), that appear in all path cover solutions. We study constrained path covers, a restriction on the path cover solution that incorporate practical constraints arising in multi-assembly problems. We give efficient algorithms finding all maximal safe paths for constrained path covers. We compute the safe paths of splicing graphs constructed from transcript annotations of different species. Our algorithms run in less than 15 seconds per species and report RNA contigs that are over 99% precise and are up to 8 times longer than unitigs. Moreover, RNA contigs cover over 70% of the transcripts and their coding sequences in most cases. With their increased length to unitigs, high precision, and fast construction time, maximal safe paths can provide a better base set of sequences for transcript assembly programs.
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| 4. |
- Chaudhury, Ayan, et al.
(författare)
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Plant Species Identification from Occluded Leaf Images
- 2020
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Ingår i: IEEE/ACM Transactions on Computational Biology & Bioinformatics. - : Institute of Electrical and Electronics Engineers (IEEE). - 1545-5963 .- 1557-9964. ; 17:3, s. 1042-1055
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Tidskriftsartikel (refereegranskat)abstract
- We present an approach to identify the plant species from the contour information from occluded leaf image using a database of full plant leaves. Although contour based 2D shape matching has been studied extensively in the last couple of decades, matching occluded leaves with full leaf databases is an open and little worked on problem. Classifying occluded plant leaves is even more challenging than full leaf matching because of large variations and complexity of leaf structures. Matching an occluded contour with all the full contours in a database is an NP-hard problem, so our algorithm is necessarily suboptimal. First, we represent the 2D contour points as a beta-Spline curve. Then, we extract interest points on these curves via the Discrete Contour Evolution (DCE) algorithm. We use subgraph matching using the DCE points as graph nodes, which produces a number of open curves for each closed leaf contour. Next, we compute the similarity transformation parameters (translation, rotation, and uniform scaling) for each open curve. We then "overlay" each open curve with the inverse similarity transformed occluded curve and use the Frechet distance metric to measure the quality of the match, retaining the best eta matched curves. Since the Frechet metric is cheap to compute but not perfectly correlated with the quality of the match, we formulate an energy functional that is well correlated with the quality of the match, but is considerably more expensive to compute. The functional uses local and global curvature, Shape Context descriptors, and String Cut features. We minimize this energy functional using a convex-concave relaxation framework. The curve among these best eta curves, that has the minimum energy, is considered to be the best overall match with the occluded leaf. Experiments on three publicly available leaf image database shows that our method is both effective and efficient, outperforming other current state-of-the-art methods. Occlusion is measured as the percentage of the overall contour (and not leaf area) that is missing. We show that our algorithm can, even for leaves with a high amounts of occlusion (say 50 percent occlusion), still identify the best full leaf match from the databases.
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| 5. |
- Dubrova, Elena, et al.
(författare)
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A SAT-Based Algorithm for Finding Attractors in Synchronous Boolean Networks
- 2011
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Ingår i: IEEE/ACM Transactions on Computational Biology & Bioinformatics. - 1545-5963 .- 1557-9964. ; 8:5, s. 1393-1399
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Tidskriftsartikel (refereegranskat)abstract
- This paper addresses the problem of finding attractors in synchronous Boolean networks. The existing Boolean decision diagram-based algorithms have limited capacity due to the excessive memory requirements of decision diagrams. The simulation-based algorithms can be applied to larger networks, however, they are incomplete. We present an algorithm, which uses a SAT-based bounded model checking to find all attractors in a Boolean network. The efficiency of the presented algorithm is evaluated by analyzing seven networks models of real biological processes, as well as 150,000 randomly generated Boolean networks of sizes between 100 and 7,000. The results show that our approach has a potential to handle an order of magnitude larger models than currently possible.
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| 6. |
- Elias, Isaac, et al.
(författare)
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A 1.375-Approximation Algorithm for Sorting by Transpositions
- 2006
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Ingår i: IEEE/ACM Transactions on Computational Biology & Bioinformatics. - 1545-5963 .- 1557-9964. ; 3:4, s. 369-379
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Tidskriftsartikel (refereegranskat)abstract
- Sorting permutations by transpositions is an important problem in genome rearrangements. A transposition is a rearrangement operation in which a segment is cut out of the permutation and pasted in a different location. The complexity of this problem is still open and it has been a 10-year-old open problem to improve the best known 1.5-approximation algorithm. In this paper, we provide a 1.375-approximation algorithm for sorting by transpositions. The algorithm is based on a new upper bound on the diameter of 3-permutations. In addition, we present some new results regarding the transposition diameter: We improve the lower bound for the transposition diameter of the symmetric group and determine the exact transposition diameter of simple permutations.
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| 7. |
- Flores, Samuel Coulbourn, et al.
(författare)
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Fast Flexible Modeling of RNA Structure Using Internal Coordinates
- 2011
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Ingår i: IEEE/ACM Transactions on Computational Biology & Bioinformatics. - 1545-5963 .- 1557-9964. ; 8:5, s. 1247-1257
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Tidskriftsartikel (refereegranskat)abstract
- Modeling the structure and dynamics of large macromolecules remains a critical challenge. Molecular dynamics (MD) simulations are expensive because they model every atom independently, and are difficult to combine with experimentally derived knowledge. Assembly of molecules using fragments from libraries relies on the database of known structures and thus may not work for novel motifs. Coarse-grained modeling methods have yielded good results on large molecules but can suffer from difficulties in creating more detailed full atomic realizations. There is therefore a need for molecular modeling algorithms that remain chemically accurate and economical for large molecules, do not rely on fragment libraries, and can incorporate experimental information. RNABuilder works in the internal coordinate space of dihedral angles and thus has time requirements proportional to the number of moving parts rather than the number of atoms. It provides accurate physics-based response to applied forces, but also allows user-specified forces for incorporating experimental information. A particular strength of RNABuilder is that all Leontis-Westhof basepairs can be specified as primitives by the user to be satisfied during model construction. We apply RNABuilder to predict the structure of an RNA molecule with 160 bases from its secondary structure, as well as experimental information. Our model matches the known structure to 10.2 Angstroms RMSD and has low computational expense.
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| 8. |
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| 9. |
- Gustafsson, Mika, 1977-, et al.
(författare)
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Constructing and analyzing a large-scale gene-to-gene regulatory network Lasso-constrained inference and biological validation
- 2005
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Ingår i: IEEE/ACM Transactions on Computational Biology & Bioinformatics. - 1545-5963 .- 1557-9964. ; 2:3, s. 254-261
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Tidskriftsartikel (refereegranskat)abstract
- We construct a gene-to-gene regulatory network from time-series data of expression levels for the whole genome of the yeast Saccharomyces cerevisae, in a case where the number of measurements is much smaller than the number of genes in the network. This network is analyzed with respect to present biological knowledge of all genes (according to the Gene Ontology database), and we find some of its large-scale properties to be in accordance with known facts about the organism. The linear modeling employed here has been explored several times, but due to lack of any validation beyond investigating individual genes, it has been seriously questioned with respect to its applicability to biological systems. Our results show the adequacy of the approach and make further investigations of the model meaningful.
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| 10. |
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