Joined July 2016
- Tweets 236
- Following 1,948
- Followers 507
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28 Photos and videos
Pinned Tweet
27 Oct 2020
Our work on DNA methylation in M. tuberculosis is finally out in @eLife! elifesciences.org/articles/5… Using sequencing kinetics and @PacBio long reads, we fully assembled DNA methylomes from 93 phylogeographically diverse clinical Mycobacterium tuberculosis complex isolates. (1/7)
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7 Jan 2025
1/ 🎉 Excited to share our lab’s latest work: “Intercellular mosaic methylation in fast-growing Mycobacterium tuberculosis clinical isolates,” now published in @NAR_Open Molecular Medicine: tinyurl.com/tb-imm
Huge thanks to my co-first author, Maryam Ahmadi Jeshvaghane!
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7 Jan 2025
11/ This work highlights how integrating biological domain knowledge with @PacBio long-read sequencing can uncover hidden information about bacterial states directly from sequencing reads. 🔎🧬➡️🧠
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7 Jan 2025
12/ Immense gratitude to Dr. Monica Espinoza, Derek Conkle-Gutierrez, @FaramarzValafar, and our @SDSUResearch colleagues for turning this curious observation into a paper that raises exciting questions and new hypotheses. #TBResearch #epigenetics #sequencing
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Sam Modlin retweeted
16 Oct 2023
Our first research paper on the genomic epidemiology of drug resistant Tuberculosis in Mexico just published! 🧬🇲🇽 Grateful for the incredible team who made this possible @cliconac, @IndGenomics, @rozecu05, Dr. Julio, Dr. Enciso #WGS
journals.plos.org/plosone/ar…
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6 Apr 2023
Very happy to have our latest work published in Drug Resistance Updates. It highlights an interesting, clinically important case where targeted molecular diagnostics fail to correctly classify drug-resistant TB due to primer evasion.
6 Apr 2023
Proud of latest article from @Valafarlab led by @sam_modlin, published by Drug Resistance Updates. We show how minority PZA-susceptible #TB population in a sample can prevent detection of the majority resistant population by targeted molecular diagnostics. doi.org/10.1016/j.drup.2023.…
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Sam Modlin retweeted
10 Feb 2023
I am proud to announce the latest article from @Valafarlab led by @0xaf1f, published by @OxfordJournals. Here, we evaluate syntenic block detection strategies, build a combined rearrangement/SNP tree for comprehensive phylogeny of clinical #tuberculosis. academic.oup.com/bioinformat…
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Sam Modlin retweeted
29 Nov 2022
Humans excel at science when they are emotionally detached from the subjects under investigation.
Emotions can pose a challenge even for self-aware people aiming for objectivity.
Protein to RNA correspondence seems to engender enough feelings to challenge objectivity. 🧵🧵🧵
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Sam Modlin retweeted
9 Nov 2022
@Kuldeep_R_Gupta, working together with @celenagwin, discovered that a protein of unknown function in mycobacteria (PgfA) is recruited to one side of the cell by our favorite protein LamA, where it coordinates lipid trafficking and fast polar growth
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Sam Modlin retweeted
9 Nov 2022
A few of us from the Single Cell Genomics team went to a stained glass workshop @ColorGlassShop. I asked the friendly sequencing lab techs in the @cnag_eu to save the used @illumina flow cells, and here is my first attempt at sci-art 🧪🎨. It could be a flower, or the sun, or...?
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2 Nov 2022
Join us in San Diego! 🌅🔬🦭🧫🐠💻🐟 Work with high-quality long read sequencing data and other cutting edge profiling of interesting TB samples. And exciting opportunities in the wet-lab to improve on current methods and test data-driven hypotheses! DM me or @FaramarzValafar
2 Nov 2022
. @Valafarlab has several predoctoral & postdoctoral positions open. We are focused on Tuberculosis. We house a wet and a dry lab. Members work on all aspects of TB Research: mutagenesis, phenotyping, informatics, ML/AI, evolution, phylogeny, systems biology, metabolic modeling
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1 Nov 2022
Cool read from @ewencallaway on protein structure AI from @Meta. My 2 cents -- Protein structures are often highly dependent on their microenvironment. Might the 60x structure prediction speed-up be most useful in exploring the context-dependence of protein structures?
1 Nov 2022
Meta just dropped 600 million protein structure predictions, made using a large language model.
My latest for @Nature
nature.com/articles/d41586-0…
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1 Nov 2022
@alexrives @ebetica Really cool stuff here. Do your methods allow for physicochemical inputs that influence or constrain the predicted model space? Or might it in the future? Studying this on a smaller set of proteins over large swaths of physicochemical space could yield insight
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