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arXiv 2021年

作者： Aizenbud, Yariv Jaffe, Ariel Wang, Meng Hu, Amber Amsel, Noah Nadler, Boaz Chang, Joseph T. Kluger, Yuval Program in Applied Mathematics Yale University New HavenCT06511 United States Department of Computer Science Weizmann Institute of Science Rehovot76100 Israel Department of Statistics Yale University New HavenCT06520 United States Interdepartmental Program in Computational Biology and Bioinformatics Yale University New HavenCT06511 United States Department of Pathology Yale University New HavenCT06511 United States

Modeling the distribution of high dimensional data by a latent tree graphical model is a prevalent approach in multiple scientific domains. A common task is to infer the underlying tree structure, given only observations of its terminal nodes. Many algorithms for tree recovery are computationally intensive, which limits their applicability to trees of moderate size. For large trees, a common approach, termed divide-and-conquer, is to recover the tree structure in two steps. First, recover the structure separately of multiple, possibly random subsets of the terminal nodes. Second, merge the resulting subtrees to form a full tree. Here, we develop Spectral Top-Down Recovery (STDR), a deterministic divide-and-conquer approach to infer large latent tree models. Unlike previous methods, STDR partitions the terminal nodes in a non random way, based on the Fiedler vector of a suitable Laplacian matrix related to the observed nodes. We prove that under certain conditions, this partitioning is consistent with the tree structure. This, in turn, leads to a significantly simpler merging procedure of the small subtrees. We prove that STDR is statistically consistent and bound the number of samples required to accurately recover the tree with high probability. Using simulated data from several common tree models in phylogenetics, we demonstrate that STDR has a significant advantage in terms of runtime, with improved or similar accuracy. Copyright © 2021, The Authors. All rights reserved.

关键词： Recovery

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Pyramid Scene Parsing Net Model for Automated Paddy Field Map using SPOT 6 Satellite Images

Pyramid Scene Parsing Net Model for Automated Paddy Field Ma...

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IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)

作者： Yaya Heryadi Edy Irwansyah Eka Miranda Haryono Soeparno Herlawati Kiyota Hashimoto Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Faculty of Technology and Environment Prince of Songkla University Phuket Thailand

Food sustainability is still one of the main priorities for many countries as it contributes to the economy and stability of the nation. For government in many countries whose peoples consumes rice as its staple food, food self-sufficiency initiatives highly depend on accurate prediction of paddy field map. Mapping paddy field task is a challenging problem which cannot be handled manually especially when the paddy fields are spread out in very wide geographical areas such as those in Indonesia. Fortunately, wide availability of satellite imagery and the advent of deep learning technology in the past ten years have made it possible to improve efficiency of most parts of those manual works involving image semantic segmentation tasks. However, satellite image-based semantic segmentation is a challenging task. High object complexity, cloud partial occlusion, larger image size than a computer memory can stored can hinder accuracy of the image segmentation results. This paper presents a method for paddy field map generating using semantic image segmentation approach in which Pyramid Scene Parsing Net model is used for segmenting satellite imagery. The generated paddy map can be used as a basis for decision-making, especially in the agricultural sector. Analysis of local land use/land cover dynamics. The results of his experiments using SPOT 6 satellite imagery from the Pahung region of Central Kalimantan achieved average training accuracy, best training accuracy and test accuracy of 0.85, 0.86 and 0.89 respectively. These results indicated that the semantic segmentation model is suitable for addressing the same task in different crops.

关键词： Training Productivity Deep learning Satellites Semantic segmentation Crops Predictive models

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Core packing of well-defined x-ray and NMR structures is the same

arXiv

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arXiv 2022年

作者： Grigas, Alex T. Liu, Zhuoyi Regan, Lynne O’Hern, Corey S. Graduate Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States Integrated Graduate Program in Physical and Engineering Biology Yale University New HavenCT06520 United States Department of Mechanical Engineering and Materials Science Yale University New HavenCT06520 United States Institute of Quantitative Biology Biochemistry and Biotechnology Centre for Synthetic and Systems Biology School of Biological Sciences University of Edinburgh United Kingdom Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States

Numerous studies have investigated the differences and similarities between protein structures determined by solution NMR spectroscopy and those determined by x-ray crystallography. A fundamental question is whether any observed differences are due to differing methodologies, or to differences in the behavior of proteins in solution versus in the crystalline state. Here, we compare the properties of the hydrophobic cores of high-resolution protein crystal structures and those in NMR structures, determined using increasing numbers and types of restraints. Prior studies have reported that many NMR structures have denser cores compared to those of high-resolution x-ray crystal structures. Our current work investigates this result in more detail, and finds that these NMR structures tend to violate basic features of protein stereochemistry, such as small non-bonded atomic overlaps and few Ramachandran and side chain dihedral angle outliers. We find that NMR structures solved with more restraints, and which do not significantly violate stereochemistry, have hydrophobic cores that have a similar size and packing fraction as their counterparts determined by x-ray crystallography at high-resolution. These results lead us to conclude that, at least regarding the core packing properties, high-quality structures determined by NMR and x-ray crystallography are the same, and the differences reported earlier are most likely a consequence of methodology, rather than fundamental differences between the protein in the two different environments. Significance: Dense packing of hydrophobic residues is key to protein structure and stability. Previously, it has been noted that structures solved by NMR spectroscopy have denser cores than x-ray crystal structures. Here, we calculate the core size and packing fraction of NMR structures with experimental restraints in the PDB. Their cores are typically smaller, but denser. However, NMR structures with accurate stereochemistry possess core pa

关键词： X ray crystallography

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Successful Hematopoietic Cell Transplantation in Patients with Fanconi Anemia with Severe Renal Insufficiency

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Transplantation and Cellular Therapy 2024年第2期30卷 S293-S294页

作者： Vasanna, Smitha Hosahalli Nelson, Kristina, PharmD Cao, Qing, MS Srikanthan, Meera Mahajan, Ruchi Wagner, John E., MD Macmillan, Margaret, MD Pediatrics Blood and Marrow Transplantation & Cellular Therapy Program University of Minnesota Minneapolis MN Department of Pharmacy University of Minnesota Masonic Children's Hospital Minneapolis MN Biostatistics and Bioinformatics Masonic Cancer Center University of Minnesota Minneapolis MN Pediatric Department of Nephrology University of Minnesota Minneapolis MN

IntroductionHematopoietic cell transplantation (HCT), the only proven cure for the hematological manifestations of Fanconi Anemia (FA) is particularly challenging in patients with renal insufficiency. ObjectiveTo analyze outcome of HCT in FA patients with pre-existent renal insufficiency MethodsThis retrospective single center cohort study reports outcomes of 20 FA patients with pre-existent renal insufficiency, defined as glomerular filtration rate (GFR) ≤70ml/min/1.73m 2 by nuclear medicine scan, who underwent HCT from 1997-2021. ResultsMedian age was 5 years (range, 0.75-24) and median GFR 51.2 ml/min/1.73m 2 (range 8-68.4). Median duration of follow up is 14.3 (range <1 month-14.3) months. Two patients received dialysis prior to HCT. HCT indications were severe marrow failure (n=16), MDS/AML (n=2), T ALL (n=1), and high risk biallelic BRCA2 genotype (n=1). Other genotypes included FANCA, B, C, D2 and unknown in 2 patients. Conditioning regimens varied by donor source and disease at time of HCT but included cyclophosphamide (CY) and mesna per institutional guidelines in all patients (Table 1) and fludarabine (FLU) in 19 patients. Four patients had no dose reduction in CY or FLU. Based on pre HCT GFR, the dose of CY was reduced by 50% in 5 patients and the dose of FLU reduced by 20% (n=6), 50% (n=4) or 75% (n=1), with 5 patients having both CY and FLU adjusted. GVHD prophylaxis included cyclosporine, T cell depletion and either methylprednisolone or mycophenolate. All but one evaluable patients achieved neutrophil engraftment at a median of 10 days (range 5 -24) after HCT. Only one patient developed grade II-IV acute GVHD, and no patient developed chronic GVHD. Six patients required dialysis during the HCT course, 2 of whom had chemotherapy dose reductions. 5 of these 6 patients died within the first 2 years after HCT. Of the 9 patients who did not have dialysis before transplant and who also received dose reduction of chemotherapy, the probability of survival at

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Retroactivity Affects the Adaptive Robustness of Transcriptional Regulatory Networks

Retroactivity Affects the Adaptive Robustness of Transcripti...

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American Control Conference

作者： Junmin Wang Calin Belta Bioinformatics Graduate Program Boston University Boston MA 02215 USA Division of Systems Engineering and the Bioinformatics Graduate Program Boston University Boston MA 02215 USA

ISBN: (纸本)9781538679012;9781538679265

Adaptation refers to the system's ability to respond transiently to an input signal and subsequently recover to the initial states. Adaptive robustness, the ability of a network to achieve adaptation, is subject to the loading effects arising from modular interconnections, known as retroactivity. Studying the effects of retroactivity on adaptive robustness facilitates the employment of retroactivity to improve circuit performance in synthetic biology. In this paper, we developed a framework for quantifying adaptive robustness via statistical model checking and used this framework to investigate the effects of retroactivity on adaptive robustness. We found that increasing retroactivity tends to raise adaptive robustness in networks where the output protein does not perform regulatory functions, such as incoherent feedforward loops.

关键词： Self tuning input signal Robustness Circuit optimization Model checking Frameworks synthetic biology Network Gene Regulatory Networks Regulatory

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Provoking Tweets by Indonesia Media Twitter in the Initial Month of Coronavirus Disease Hit

Provoking Tweets by Indonesia Media Twitter in the Initial M...

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International Conference on Information Management and Technology (ICIMTech)

作者： Ika Nurlaila Reza Rahutomo Kartika Purwandari Bens Pardamean BINUS Online Learning Bina Nusantara University Jakarta Indonesia Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

After months in denial, on 2 nd March 2020 the first case of COVID-19 in Indonesia was announced and soon was declared as a national pandemic. COVID-19 was since being the headlines of the news offline and online. This trigger either positive or negative responses from the readers, which in turn affect at least the depth of understanding and furthermore the effectiveness of any enforced intervention taken with the purpose to control the transmission of the COVID-19. In order to assess how likely the COVID-19-containing news being forwarded to reach more readers and how the pertinent news bridge further virtual interaction, we crawled data from Twitter as the major online microblogging platform to analyze how likely COVID-19-containing tweets were echoed and what typical tweet about COVID-19 that gained attentions. This is critical to evaluate how people virtually responded against the tweets. Our analyzed data is visualized using Matplotlib by Python and Graph Prism8 accordingly. We figured out that timing and number of followers are not determinative for the tweets being retweeted. Instead, provoking headline add likelihood for the tweets to be moving forward. Also appeared in our analysis that the top two media (Detik and Kompas) shared the same proportion on their tweet type fractions on where information dominated the fraction of their tweets.

关键词： Twitter Media Corona Tagging Diseases Data visualization

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Validation Requirements for AI-based Intervention-Evaluation in Aging and Longevity Research and Practice

arXiv

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arXiv 2024年

作者： Fuellen, Georg Kulaga, Anton Lobentanzer, Sebastian Unfried, Maximilian Avelar, Roberto A. Palmer, Daniel Kennedy, Brian K. Institute for Biostatistics and Informatics in Medicine and Ageing Research Rostock University Medical Center Rostock Germany UCD Conway Institute of Biomolecular and Biomedical Research School of Medicine University College Dublin Dublin Ireland Institute for Computational Biomedicine Heidelberg University Faculty of Medicine Heidelberg University Hospital Heidelberg Germany European Bioinformatics Institute Hinxton Cambridgeshire United Kingdom Healthy Longevity Translational Research Program Yong Loo Lin School of Medicine National University of Singapore Singapore Department of Biochemistry Yong Loo Lin School of Medicine National University of Singapore Singapore Department of Physiology Yong Loo Lin School of Medicine National University of Singapore Singapore

The field of aging and longevity research is overwhelmed by vast amounts of data, calling for the use of Artificial Intelligence (AI), including Large Language Models (LLMs), for the evaluation of geroprotective interventions. Such evaluations should be correct, useful, comprehensive, explainable, and they should consider causality, interdisciplinarity, adherence to standards, longitudinal data and known aging biology. In particular, comprehensive analyses should go beyond comparing data based on canonical biomedical databases, suggesting the use of AI to interpret changes in biomarkers and outcomes. Our requirements motivate the use of LLMs with Knowledge Graphs and dedicated workflows employing, e.g., Retrieval-Augmented Generation. While naive trust in the responses of AI tools can cause harm, adding our requirements to LLM queries can improve response quality, calling for benchmarking efforts and justifying the informed use of LLMs for advice on longevity *** Codes 68T01 General topics in artificial intelligence © 2024, CC BY.

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Structural basis of water-mediated cis Watson-Crick/Hoogsteen base-pair formation in non-CpG methylation

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Nucleic acids research 2024年第14期52卷 8566-8579页

作者： Shan-Meng Lin Hsiang-Ti Huang Pei-Ju Fang Chi-Fon Chang Roshan Satange Chung-Ke Chang Shan-Ho Chou Stephen Neidle Ming-Hon Hou Graduate Institute of Genomics and Bioinformatics National Chung Hsing University Taichung 402 Taiwan. Genomics Research Center Academia Sinica Taipei 115 Taiwan. Taiwan Biobank Institute of Biomedical Sciences Academia Sinica Taipei 115 Taiwan. Institute of Biochemistry National Chung Hsing University Taichung 402 Taiwan. School of Pharmacy University College London London WC1N 1AX UK. Doctoral Program in Medical Biotechnology National Chung Hsing University Taichung 402 Taiwan. Graduate Institute of Biotechnology National Chung Hsing University Taichung 402 Taiwan. Department of Life Sciences National Chung Hsing University Taichung 402 Taiwan. Biotechnology Center National Chung Hsing University Taichung 402 Taiwan.

Non-CpG methylation is associated with several cellular processes, especially neuronal development and cancer, while its effect on DNA structure remains unclear. We have determined the crystal structures of DNA duplexes containing -CGCCG- regions as CCG repeat motifs that comprise a non-CpG site with or without cytosine methylation. Crystal structure analyses have revealed that the mC:G base-pair can simultaneously form two alternative conformations arising from non-CpG methylation, including a unique water-mediated cis Watson-Crick/Hoogsteen, (w)cWH, and Watson-Crick (WC) geometries, with partial occupancies of 0.1 and 0.9, respectively. NMR studies showed that an alternative conformation of methylated mC:G base-pair at non-CpG step exhibits characteristics of cWH with a syn-guanosine conformation in solution. DNA duplexes complexed with the DNA binding drug echinomycin result in increased occupancy of the (w)cWH geometry in the methylated base-pair (from 0.1 to 0.3). Our structural results demonstrated that cytosine methylation at a non-CpG step leads to an anti→syntransition of its complementary guanosine residue toward the (w)cWH geometry as a partial population of WC, in both drug-bound and naked mC:G base pairs. This particular geometry is specific to non-CpG methylated dinucleotide sites in B-form DNA. Overall, the current study provides new insights into DNA conformation during epigenetic regulation.

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Pre-Treatment Higher Eosinophil Count Is Associated with Improved Survival after Autologous CAR-T Therapy for Hematologic Malignancies

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Transplantation and Cellular Therapy 2025年第2期31卷 S334-S334页

作者： Kagalwalla, Sana, MD Sumransub, Nuttavut, MD Cao, Qing, MS Hu, Marie, MD Tracy, Sean, MD, PhD O'Leary, Daniel, MD Maakaron, Joseph E., MD Juckett, Mark Bachanova, Veronika Department of Medicine University of Minnesota Minneapolis MN Division of Hematology Oncology and Transplantation University of Minnesota Minneapolis MN Biostatistics and Bioinformatics Masonic Cancer Center University of Minnesota Minneapolis MN Bone and Marrow Transplant Program University of Minnesota Medical Center Minneapolis MN Division of Hematology Oncology and Transplantation University of Minnesota Minneapolis MN

IntroductionEosinophils (Eo) play an important role in recruiting T-cells to tumors, and recently were associated with an improved response to immune checkpoint inhibitor therapy. Preclinical studies showed that combining stem cell-derived eosinophil therapy with CAR-T leads to improved treatment efficacy. Limited clinical observations reported that patients greater eosinophil counts after CAR-T had superior CR rate and survival. We therefore examined associations between eosinophil count and immunologic recovery pre and post CAR-T cell therapy and treatment outcomes. MethodsWe included consecutive patients (>18 yrs) with leukemia, lymphoma or myeloma treated between January 2018 and June 2023 on the observational phase 2 study using commercial CAR-T products targeting CD19 and BCMA (NCT03642626). We collected CAR-T related toxicities, history of autoimmune diseases, peak absolute and percentage eosinophil counts and lymphocyte subset before aphaeresis, CAR-T cell therapy and at ∼30, 60, and 100 days after CAR-T infusion. Analysis of categorical variables was performed by Chi-square and of continuous variables by Wilcoxon rank-sum tests. Recursive partitioning methods were used to find the optimal eosinophil count cutoff based on two-year overall survival (OS) and progression-free survival (PFS). ResultsWe included 106 patients with a median age of 62.3 years (range 19-86), 61% were male, 66% had DLBCL. Peak eosinophil count varied widely among patients at baseline (0-2400 cells/μl), median was 200 cells/μl. Using recursive partitioning, pre-apheresis Eo count 150 determined the high eosinophil group (n=56, 53%; median eo count of 300 (range 100-2400) and low eo group (n=50, 47%, median 100; range 0 - 100 cells/μl). Baseline characteristics of the two groups were similar except in the low eo group, more patients had pre-existing autoimmune condition (34% vs 11%; P<0.01), and high ferritin levels. Eo levels (hi vs low) were not associated with CR rate (76% vs 66%) no

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K-Means Clustering Model to Discriminate Copper-Resistant Bacteria as Bioremediation Agents

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Procedia Computer Science 2021年 179卷 804-812页

作者： Ika Nurlaila Wahyu Irawati Kartika Purwandari Bens Pardamean Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480 Department of Biology Education Faculty of Education Pelita Harapan University Tangerang Indonesia 15811 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Copper (Cu) has been excessively used for some valuable commodities and this creates environmental problems. The inorganic element becomes toxic when presents beyond the recommended tolerated concentration. Bacterial-based remediation is seen to be an excellent tool to overcome it as it reduces the copper contamination without yielding any other forms of contamination. There are some pivotal properties in the bacteria render them being considered as bioremediation agents against coppers contamination, namely bioaccumulation and biosorption. In the present study, we question if these bacteria could be clustered into a strong and representative proximity according to their functional properties. Mostly, bacteria are grouped based on their genetic profiles derived from the 16S rRNA sequencing. We propose that our K-Means clustering model can be employed to identify genetically-unlabelled bacteria. But first, a prominent reference should be developed and we are in this phase. We figured out the K-Means clustering model do not pull the same-genus bacteria into the same cluster. Instead, the model gathers into a proximity those isolates with similarity on a functional characteristic termed minimum inhibitory concentration (MIC), regardless their origins and their hierarchy in taxonomy.

关键词： Copper-Resistant Bacteria K-Means Minimum Inhibitory Concentration

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