04/11, [Project update] NSF Division of Labor (2) (Yoonmi and Seyoung)
Yoonmi: TBA
Seyoung: TBA
03/28, [Project update] NSF Division of Labor (1) (Steve and Mahsa)
Steve: TBA
Mahsa: TBA
03/14, [Project update] DOE Bioavailable Organic Matter (Mano and Hugh)
Mano: Integrating Key Traits Governing Bioavailability into Substrate Explicit Thermodynamic Modeling for Estimating Maximal Growth Rates in River Sediments
Hugh: Characterization of chemical traits and transformations in predicted bioavailable organic matter from bootstrapped, metagenome-informed Substrate Explicit Thermodynamic Modeling (SXTM)
02/28, [Project update] NCESR Deep Subsurface (Sanjogand Jackfin)
Sanjog: Integrating Genomics and Thermodynamics to Model Microbially-Mediated Hydrogen Dynamics in the Deep Subsurface
Jackfin: The use of ‘Phydon’ and ‘GenomeSPOT’ in calculating different traits of microbial species using genomes
01/31, Hugh, Mano, and Hyun, Tips for effective literature survey
2024
12/03, Rawan Elabd, Flux balance analysis of E. coli
11/19, Insoo Jeon, Disease suppressive soil microbiome associated with maize and Puccinia polysora
Development of methods to assess disease severity
Data collection to interpret phenotype using microbiome analysis
Training and preparation of metabolic modeling and bioinformatics
11/05, Jackfin KC, Overview of the lambda modeling
10/15, Sanjog Kharel, Estimating u_max from genome data using gRodon
10/01: Jackfin KC, Updates on Android app development
09/09: [Special Seminar] Ms. Miao He from Tokyo Metropolitan University, Syntrophic Association Between Purple Photosynthetic Bacteria and Tetrathionate-Reducing Bacteria
08/16: [Special Seminar] Dr. Mayumi Seto from Nara Women's University, Prediction of microbial redox functions based on thermodynamics and causal inference
08/12-16: Song Lab - Bioinformatics and Modeling Workshop (SL-BMW) led by Hugh McCullough
07/09: Sanjog Kharel, Modelling microbial dynamics in deep subsurface via their energetics
07/03: Yoonmi Choi, Current Status of Plant Modeling: Approaches and Insights
06/25: Insoo Jeon, Plant-driven assembly of disease-suppressive soil microbiomes
06/18: Steve Zhang and Mahsa Mohammadi, ASM highlights
06/06: Steve Zhang and Mahsa Mohammadi, ASM dry run
05/21: Manokaran Veeramani, Bioavailable OM selection to improve predictions of aerobic respiration in river corridors
05/14: Sanjog Kharel, Yoonmi Choi, and Mahsa Mohammadi, BSEN 951 Term Project Presentations
05/07: Manokaran Veeramani, Computational inference of spatial microbial interactions from microscopic images
04/30: Steve Zhang, Building Metabolite-Enzyme Networks using edgeR and NetCom: Functional Enrichment in RSAX and WSAX
04/23: Mahsa Mohammadi, The Impact of Red and White Sorghum Arabinoxylans on Human Gut Microbiota Interactions
04/09: Aimee Kessell, Genome-scale network modeling of chitin-degrading microbial communities and their isolates (thesis defense)
03/26: Aimee Kessell, Genome-scale network modeling of chitin-degrading microbial communities and their isolates (presentation to the Soil Microbiome SFA at PNNL, dry run #2)
03/19: Aimee Kessell, Genome-scale network modeling of chitin-degrading microbial communities and their isolates (dry run #1)
02/27: Sanjog Kharel, Chemolithotrophs in deep subsurface
02/13: Hugh McCullough, Redox Homeostasis and Potential Indicators of Oxidative Stress in Omics Data
02/06: Mahsa Mohammadi, Network-based analysis of metagenomics data
01/30: Steve Zhang, Update: Community Flux Coupling Analysis in Unicyanobacterial Communities
01/23: Kiera Chan, Novel Eigenmode-Based Feature Engineering for Efficient and Interpretable Image Classification: Application to Handwritten Digits
01/10: Sanjog Kharel, Lambda Model for Microbial Growth (2): Identification of bioavailable OM
2023
12/19: Andrea Mikulasova, Flux Balance Analysis: Everything I didn’t know
11/28: Manokaran Veeramani, Overview of similarity measures/metrics for comparing spatial data
11/21: Hugh McCullough, Clustering of River Samples by Functional Traits identified by DRAM
11/14: Aimee Kessell, Isolate and Community Model Updates – Improvements and Drawbacks
10/31: Mahsa Mohammadi, Combination of kinetic-based modeling and metabolic network modeling
10/26: Steve Zhang, Combining KIDI with SteadyCom in Modeling Unicyanobacterial Communities
10/19: Sanjog Kharel, Lambda model for microbial growth
10/12: Toko Hisano, How do incomplete denitrifying bacteria survive in nature?
09/26: Hugh McCullough, Intersections of reaction activity from model predictions and omics data
09/19: Aimee Kessell, Predicting flux within a community via SteadyCom
09/12: Manokaran Veeramani, Inference of Spatial Interactions from Long-Term Image Data
09/05: Mahsa Mohammadi, Review of LIMITS algorithm
08/28: Yoan Ghaffar, Residents' impact on the indoor environment; Kiera Chan, Applying Singular Value Decomposition to Extract Shape Features in Handwritten Digits
08/21: Steve Zhang, Modeling of Metabolism and Autotroph-Heterotroph Interactions in UCC-A and UCC-O
08/14: Hugh McCullough, Soil microbiome responses to environmental perturbations
07/17: Aimee Kessell, Impacts of Bioenergetic Costs of Chitin Decomposition on Degrader Metabolism and Their Interactions with Cheaters
07/03: Huisun Eom, Data-Driven Modeling using SINDy: Application to Biological data and Education-related Data
06/26: Soo Park, Differential response of nitrate-reducing synthetic communities to varying carbon-to-nitrogen ratio
06/05: [Special Seminar] Dr. Sridharakumar Narasimhan at IIT Madras, A Priori Parameter Identifiability - Impact of Measurements in Complex Reaction Networks
05/29: All, 2023 Summer and Beyond
05/22: Manokaran Veeramani, Stochastic simulations for modeling chemical reactions (II)
05/15: Ayeon Park, App development for modeling and simulation of interactions between microbial populations
05/08: Manokaran Veeramani, Stochastic simulations for modeling chemical reactions (I)
05/01: Mahsa Mohammadi, Comparative Study of the Effects of Red and White Sorghum Arabinoxylans on Human Gut Microbiota: Data-Driven Approach
04/24: Steve Zhang, Pathway and Flux Coupling Analysis in Unicyanobacterial Communities
04/10: Hugh McCullough, Structure of Fecal Microbial Communities under Varying Carbohydrate Compositions and Antibiotic Perturbation
04/03: Aimee Kessell, Flux Coupling Analysis – Existing algorithms and new strategies
03/27: Naeun Lee, Metabolic Network Modeling to Unravel the Impact of Copper Deficiency and High-fat Diet on Liver Metabolism
03/20: Firnaaz Ahamed, Coupled flux balance analysis and reactive transport modeling using machine learning
02/27: Soo Park, Changes of N cycling synthetic microbial communities under varying C/N ratios
02/13: Manokaran Veeramani, Modeling of context-dependent microbial interactions in biopolymer degradation networks
02/06: Soo Park, Tutorial: Bipartite graphs using NetworkX and Gephi & Mapping genes onto KEGG pathway using KEGG Color Mapper
01/23: Firnaaz Ahamed, What are the major chemical traits that govern the bioavailability of organic matters in river corridors?
01/09: Kiera Chan, Coupling the Cybernetic Modeling with Flux Balance Analysis for Dynamic Simulation of Overflow Metabolism in Escherichia coli
2022
12/21: Soo Park, C/N ratio of substrate drives the structure of microbial communities in soil
12/12: Mahsa Mohammadi, A brief review of network analysis methods for studying microbial communities
11/28: Hugh McCullough, Media carbohydrate composition’s potential Influence on variability of community assembly and peptide utilization
11/07: Steve Zhang, Flux coupling analysis: Methods and applications
10/31: Aimee Kessell, Constructing a binary metabolic network model to more accurately represent consortium growth on chitin, and its monomer, NAG
10/03: Naeun Lee, DEG-integrated modeling to increase consistency between gene expression data and flux distribution
09/19: Meeting with Dr. Shin Haruta from Tokyo Metropolitan University
08/22: Firnaaz Ahamed, Data-driven optimization allows identification of organic matters governing microbial respiration in river corridors
08/08: Hugh McCullough, Community simplification in vitro: enrichment cultures trend from stochastic to deterministic effects
[Hereafter, every other Monday]
07/22: Steve Zhang, Microbial Division of Labor in Polysaccharide-Degrading Communities
07/15: Aimee Kessell, Omics inclusion for an improved model of a chitin-degrading binary consortium
01/07: Steve Zhang, Tutorial session: Flux balance and variance analysis using CPLEX in Python
2021
12/17: Michael Israel, Cybernetic Modeling Ⅱ & Steve Zhang, Flux Balance and Variance Analysis with CPLEX in Python
12/03: Aimee Kessell, TBA
11/19: Firnaaz Ahamed, Literature review: Can ensemble modeling improve uncertainties in metabolic network reconstruction?
11/12: Naeun Lee, Identification of impacts by high-fat diet and Cu deficiency via FVA and flux sampling
11/05: Hugh McCullough, AIChE Presentation Practice / Microbiome Meta-Ecosystems and Meta-communities
10/29: Michael Israel, Cybernetic Modeling
10/15: Steve Zhang, FBA
10/08: Aimee Kessell, A Deeper Look into Microbial Cross-Feeding to Expanding the Metabolic Niche of Bacteria
10/01: Firnaaz Ahamed, Predicting organic matter thermodynamics and respiration kinetics via elemental composition of metabolomics data
09/24: Naeun Lee, Modeling of Cu deficiency in the liver with a high-fat diet, and expected changes of enzymes
09/17: Hugh McCullough, Cultivating and Identifying Interactions of Adjacent Bacterial Communities
09/10: Aimee Kessell, Metabolic Network Modeling Helps Determine Interactions In A Complex Polysaccharide-Decomposing Microbial Community
09/03: Firnaaz Ahamed, Metabolic network reconstruction using omics-enabled global gapfilling (OMEGGA) approach
08/27: Naeun Lee, Preprocessing for integration of transcriptomic data into the model & Ten rules for organized paper
08/20: Hugh McCullough, Paper Share: Challenges in microbial network construction and analysis / Bio Image analysis with ilastik
08/13: Ab Rauf Shah, Disentangling soil microbiome functions by Interkingdom Modeling
07/30: Aimee Kessell, dry-run MPA presentation
07/23: Naeun Lee, dry-run MPA presentation
07/09: Firnaaz Ahamed, Comparison between variance-based local sensitivity and density-based global sensitivity analysis
07/02: Steve Zhang, Using SINDy and PAWN to Create Equations Predicting the D-Value and Evaluate Sensitivity of Environmental Factors
06/25: Naeun Lee, Omics and metabolic network integration to predict the impacts of Cu limitation on the liver functions and energy metabolism
06/11: Hugh McCullough, Considerations for experimental models to improve culture of microbial communities
06/01-02: [Hands-on Training] Dr. Joon-Yong Lee from PNNL, KBase app development using SDK
05/21: Ab Rauf Shah, Tutorial session (II) on "making gap-free genome-scale models"
05/14: Ab Rauf Shah, Tutorial session (I) on "making gap-free genome-scale models"
05/07: All, Summer Plan Sharing
04/30: Aimee Kessell, Fungal annotation and modeling
04/23: Firnaaz Ahamed, Science in PNNL River Corridor SFA
04/16: Ab Rauf Shah, Reconstruction and Analysis of Maize root-specific metabolic models captures the programming of metabolism through multiple root types and developmental stages
04/09: Steve Zhang, Pathogen Inactivation in Meats
04/02: Naeun Lee, Suggestion of the possibility that SSAO and BMP7 may be associated with Cu-deficiency adaptive response
03/26: Puranjit Singh, Understanding multiscale model of fungal growth and its regulation (2)
03/19: Puranjit Singh, Understanding multiscale model of fungal growth and its regulation (1)
03/12: Hugh McCullough, Mucins and their role in spatial heterogeneity of gut microbiota
03/05: Aimee Kessell, Science in PNNL Soil Microbiome SFA
02/26: Firnaaz Ahamed, Modeling microbial competition potentially explains priming effects in soil ecosystem and hyporheic corridor
02/19: Steve Zhang, Using SINDY and sparse regression to predict D- values and parameters
02/12: Naeun Lee, Copper in Lipid Metabolism and Energy Homeostasis & Analysis Liver Transcriptomics Data in Matlab